Bugs by prof fixed 2

59 files changed, 435 insertions, 813 deletions

diff --git a/demos/lsqlin.dem.sce b/demos/lsqlin.dem.sce
index d417bf0..fb4bad9 100644
--- a/demos/lsqlin.dem.sce
+++ b/demos/lsqlin.dem.sce
@@ -21,8 +21,10 @@ b = [0.5251
 0.2026
 0.6721];
 [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin(C,d,A,b)
+// Press ENTER to continue
 halt()   // Press return to continue
  
+//A basic example for equality, inequality and bounds
 C = [0.9501    0.7620    0.6153    0.4057
 0.2311    0.4564    0.7919    0.9354
 0.6068    0.0185    0.9218    0.9169
@@ -44,6 +46,4 @@ beq = 4;
 lb = -0.1*ones(4,1);
 ub = 2*ones(4,1);
 [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin(C,d,A,b,Aeq,beq,lb,ub)
-halt()   // Press return to continue
- 
 //========= E N D === O F === D E M O =========//
diff --git a/demos/lsqnonneg.dem.sce b/demos/lsqnonneg.dem.sce
index b61af0a..73fa6df 100644
--- a/demos/lsqnonneg.dem.sce
+++ b/demos/lsqnonneg.dem.sce
@@ -15,6 +15,4 @@ d = [
 0.0747
 0.8405];
 [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg(C,d)
-halt()   // Press return to continue
- 
 //========= E N D === O F === D E M O =========//
diff --git a/demos/qpipopt.dem.sce b/demos/qpipopt.dem.sce
index d929a5c..41b8314 100644
--- a/demos/qpipopt.dem.sce
+++ b/demos/qpipopt.dem.sce
@@ -20,6 +20,7 @@ nbCon = 5;
 x0 = repmat(0,nbVar,1);
 param = list("MaxIter", 300, "CpuTime", 100);
 [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param)
+// Press ENTER to continue
 halt()   // Press return to continue
  
 //Find the value of x that minimize following function
@@ -39,6 +40,4 @@ ub = [%inf; %inf];
 nbVar = 2;
 nbCon = 3;
 [xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
-halt()   // Press return to continue
- 
 //========= E N D === O F === D E M O =========//
diff --git a/demos/qpipoptmat.dem.sce b/demos/qpipoptmat.dem.sce
index 61263a8..bbaa42c 100644
--- a/demos/qpipoptmat.dem.sce
+++ b/demos/qpipoptmat.dem.sce
@@ -3,26 +3,6 @@ mode(1)
 // Demo of qpipoptmat.sci
 //
 
-//Find x in R^6 such that:
-halt()   // Press return to continue
- 
-Aeq= [1,-1,1,0,3,1;
--1,0,-3,-4,5,6;
-2,5,3,0,1,0];
-beq=[1; 2; 3];
-A= [0,1,0,1,2,-1;
--1,0,2,1,1,0];
-b = [-1; 2.5];
-lb=[-1000; -10000; 0; -1000; -1000; -1000];
-ub=[10000; 100; 1.5; 100; 100; 1000];
-x0 = repmat(0,6,1);
-param = list("MaxIter", 300, "CpuTime", 100);
-//and minimize 0.5*x'*Q*x + p'*x with
-f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
-[xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param)
-clear H f A b Aeq beq lb ub;
-halt()   // Press return to continue
- 
 //Find the value of x that minimize following function
 // f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2
 // Subject to:
@@ -37,6 +17,22 @@ b = [2; 2; 3];
 lb = [0; 0];
 ub = [%inf; %inf];
 [xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub)
+// Press ENTER to continue
 halt()   // Press return to continue
  
+//Find x in R^6 such that:
+Aeq= [1,-1,1,0,3,1;
+-1,0,-3,-4,5,6;
+2,5,3,0,1,0];
+beq=[1; 2; 3];
+A= [0,1,0,1,2,-1;
+-1,0,2,1,1,0];
+b = [-1; 2.5];
+lb=[-1000; -10000; 0; -1000; -1000; -1000];
+ub=[10000; 100; 1.5; 100; 100; 1000];
+x0 = repmat(0,6,1);
+param = list("MaxIter", 300, "CpuTime", 100);
+//and minimize 0.5*x'*Q*x + p'*x with
+f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
+[xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param)
 //========= E N D === O F === D E M O =========//
diff --git a/demos/symphony.dem.sce b/demos/symphony.dem.sce
index c17c14d..0449b3a 100644
--- a/demos/symphony.dem.sce
+++ b/demos/symphony.dem.sce
@@ -24,6 +24,7 @@ xopt = [1 1 0 1 7.25 0 0.25 3.5]
 fopt = [8495]
 // Calling Symphony
 [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1)
+// Press ENTER to continue
 halt()   // Press return to continue
  
 // An advanced case where we set some options in symphony
@@ -107,7 +108,5 @@ xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 ..
 // Optimal value
 fopt = [ 24381 ]
 // Calling Symphony
-[x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options)
-halt()   // Press return to continue
- 
+[x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options);
 //========= E N D === O F === D E M O =========//
diff --git a/demos/symphonymat.dem.sce b/demos/symphonymat.dem.sce
index 0c968a7..9467e78 100644
--- a/demos/symphonymat.dem.sce
+++ b/demos/symphonymat.dem.sce
@@ -17,6 +17,7 @@ beq = [ 25, 1.25, 1.25]
 intcon = [1 2 3 4];
 // Calling Symphony
 [x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub)
+// Press ENTER to continue
 halt()   // Press return to continue
  
 // An advanced case where we set some options in symphony
@@ -99,6 +100,4 @@ xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 ..
 fopt = [ 24381 ]
 // Calling Symphony
 [x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options);
-halt()   // Press return to continue
- 
 //========= E N D === O F === D E M O =========//
diff --git a/help/en_US/lsqlin.xml b/help/en_US/lsqlin.xml
index 1216bae..1936e11 100644
--- a/help/en_US/lsqlin.xml
+++ b/help/en_US/lsqlin.xml
@@ -24,11 +24,11 @@
 <refsynopsisdiv>
    <title>Calling Sequence</title>
    <synopsis>
-   x = lsqlin(C,d,A,b)
-   x = lsqlin(C,d,A,b,Aeq,beq)
-   x = lsqlin(C,d,A,b,Aeq,beq,lb,ub)
-   x = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0)
-   x = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0,param)
+   xopt = lsqlin(C,d,A,b)
+   xopt = lsqlin(C,d,A,b,Aeq,beq)
+   xopt = lsqlin(C,d,A,b,Aeq,beq,lb,ub)
+   xopt = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0)
+   xopt = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0,param)
    [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin( ... )
    
    </synopsis>
@@ -66,9 +66,9 @@
    <varlistentry><term>exitflag :</term>
       <listitem><para> Integer identifying the reason the algorithm terminated.</para></listitem></varlistentry>
    <varlistentry><term>output :</term>
-      <listitem><para> Structure containing information about the optimization.</para></listitem></varlistentry>
+      <listitem><para> Structure containing information about the optimization. Right now it contains number of iteration.</para></listitem></varlistentry>
    <varlistentry><term>lambda :</term>
-      <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).</para></listitem></varlistentry>
+      <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.</para></listitem></varlistentry>
    </variablelist>
 </refsection>
 
@@ -82,14 +82,14 @@ Search the minimum of a constrained linear least square problem specified by :
 \begin{eqnarray}
 &amp;\mbox{min}_{x}
 &amp; 1/2||C*x - d||_2^2  \\
-&amp; \text{subject to} &amp; A.x \leq b \\
-&amp; &amp; Aeq.x \leq beq \\
+&amp; \text{subject to} &amp; A*x \leq b \\
+&amp; &amp; Aeq*x = beq \\
 &amp; &amp; lb \leq x \leq ub \\
 \end{eqnarray}
 </latex>
    </para>
    <para>
-We are calling IPOpt for solving the linear least square problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.
+We are calling IPOpt for solving the linear least square problem, IPOpt is a library written in C++.
    </para>
    <para>
 </para>
@@ -116,6 +116,7 @@ b = [0.5251
 0.2026
 0.6721];
 [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin(C,d,A,b)
+// Press ENTER to continue
 
    ]]></programlisting>
 </refsection>
@@ -123,6 +124,7 @@ b = [0.5251
 <refsection>
    <title>Examples</title>
    <programlisting role="example"><![CDATA[
+//A basic example for equality, inequality and bounds
 C = [0.9501    0.7620    0.6153    0.4057
 0.2311    0.4564    0.7919    0.9354
 0.6068    0.0185    0.9218    0.9169
@@ -144,7 +146,6 @@ beq = 4;
 lb = -0.1*ones(4,1);
 ub = 2*ones(4,1);
 [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin(C,d,A,b,Aeq,beq,lb,ub)
-
    ]]></programlisting>
 </refsection>
 
diff --git a/help/en_US/lsqnonneg.xml b/help/en_US/lsqnonneg.xml
index 95c8da1..daf79bf 100644
--- a/help/en_US/lsqnonneg.xml
+++ b/help/en_US/lsqnonneg.xml
@@ -24,8 +24,8 @@
 <refsynopsisdiv>
    <title>Calling Sequence</title>
    <synopsis>
-   x = lsqnonneg(C,d)
-   x = lsqnonneg(C,d,param)
+   xopt = lsqnonneg(C,d)
+   xopt = lsqnonneg(C,d,param)
    [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg( ... )
    
    </synopsis>
@@ -47,9 +47,9 @@
    <varlistentry><term>exitflag :</term>
       <listitem><para> Integer identifying the reason the algorithm terminated.</para></listitem></varlistentry>
    <varlistentry><term>output :</term>
-      <listitem><para> Structure containing information about the optimization.</para></listitem></varlistentry>
+      <listitem><para> Structure containing information about the optimization. Right now it contains number of iteration.</para></listitem></varlistentry>
    <varlistentry><term>lambda :</term>
-      <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).</para></listitem></varlistentry>
+      <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.</para></listitem></varlistentry>
    </variablelist>
 </refsection>
 
@@ -68,7 +68,7 @@ Solves nonnegative least-squares curve fitting problems specified by :
 </latex>
    </para>
    <para>
-We are calling IPOpt for solving the nonnegative least-squares curve fitting problems, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.
+We are calling IPOpt for solving the nonnegative least-squares curve fitting problems, IPOpt is a library written in C++.
    </para>
    <para>
 </para>
@@ -77,7 +77,7 @@ We are calling IPOpt for solving the nonnegative least-squares curve fitting pro
 <refsection>
    <title>Examples</title>
    <programlisting role="example"><![CDATA[
-A basic lsqnonneg problem
+// A basic lsqnonneg problem
 C = [
 0.0372    0.2869
 0.6861    0.7071
@@ -89,7 +89,6 @@ d = [
 0.0747
 0.8405];
 [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg(C,d)
-
    ]]></programlisting>
 </refsection>
 
diff --git a/help/en_US/master_help.xml b/help/en_US/master_help.xml
index 999a2d7..e59ac6c 100644
--- a/help/en_US/master_help.xml
+++ b/help/en_US/master_help.xml
@@ -4,10 +4,8 @@
 <!ENTITY a3d4ec65684b561d91f7a255acd23f51c SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/lsqlin.xml">
 <!ENTITY aa4a031935f5eed6cfc8fc4a49823b00b SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/lsqnonneg.xml">
 <!ENTITY a6b85f6e0c98751f20b68663a23cb4cd2 SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/qpipopt.xml">
-<!ENTITY a44928acec52adf395379e18fcff06730 SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/qpipopt_mat.xml">
 <!ENTITY a8549a3935858ed104f4749ca2243456a SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/qpipoptmat.xml">
 <!ENTITY aca972f273143ecb39f56b42e4723ac67 SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/symphony.xml">
-<!ENTITY a9953e61e8dd264a86df73772d3055e7f SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/symphony_mat.xml">
 <!ENTITY a9910ada35b57b0581e8a77d145abac4a SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/symphonymat.xml">
 <!ENTITY acc223314e8a8bc290a13618df33a6237 SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/Symphony Native Function/sym_addConstr.xml">
 <!ENTITY a5e032b3334f53385f0ce250f0d5c18f2 SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/Symphony Native Function/sym_addVar.xml">
@@ -86,10 +84,8 @@
 &a3d4ec65684b561d91f7a255acd23f51c;
 &aa4a031935f5eed6cfc8fc4a49823b00b;
 &a6b85f6e0c98751f20b68663a23cb4cd2;
-&a44928acec52adf395379e18fcff06730;
 &a8549a3935858ed104f4749ca2243456a;
 &aca972f273143ecb39f56b42e4723ac67;
-&a9953e61e8dd264a86df73772d3055e7f;
 &a9910ada35b57b0581e8a77d145abac4a;
 <chapter xml:id='section_508f0b211d17ea6769714cc144e6b731'>
 <title>Symphony Native Functions</title>
diff --git a/help/en_US/qpipopt.xml b/help/en_US/qpipopt.xml
index c0756f8..d9a0e6e 100644
--- a/help/en_US/qpipopt.xml
+++ b/help/en_US/qpipopt.xml
@@ -64,9 +64,9 @@
    <varlistentry><term>exitflag :</term>
       <listitem><para> Integer identifying the reason the algorithm terminated.</para></listitem></varlistentry>
    <varlistentry><term>output :</term>
-      <listitem><para> Structure containing information about the optimization.</para></listitem></varlistentry>
+      <listitem><para> Structure containing information about the optimization. Right now it contains number of iteration.</para></listitem></varlistentry>
    <varlistentry><term>lambda :</term>
-      <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).</para></listitem></varlistentry>
+      <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.</para></listitem></varlistentry>
    </variablelist>
 </refsection>
 
@@ -87,7 +87,7 @@ find the minimum of f(x) such that
 </latex>
    </para>
    <para>
-We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.
+We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++.
    </para>
    <para>
 </para>
@@ -113,6 +113,7 @@ nbCon = 5;
 x0 = repmat(0,nbVar,1);
 param = list("MaxIter", 300, "CpuTime", 100);
 [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param)
+// Press ENTER to continue
 
    ]]></programlisting>
 </refsection>
@@ -137,7 +138,6 @@ ub = [%inf; %inf];
 nbVar = 2;
 nbCon = 3;
 [xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
-
    ]]></programlisting>
 </refsection>
 
diff --git a/help/en_US/qpipopt_mat.xml b/help/en_US/qpipopt_mat.xml
deleted file mode 100644
index 7dec2b1..0000000
--- a/help/en_US/qpipopt_mat.xml
+++ /dev/null
@@ -1,142 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-
-<!--
- *
- * This help file was generated from qpipopt_mat.sci using help_from_sci().
- *
- -->
-
-<refentry version="5.0-subset Scilab" xml:id="qpipopt_mat" xml:lang="en"
-          xmlns="http://docbook.org/ns/docbook"
-          xmlns:xlink="http://www.w3.org/1999/xlink"
-          xmlns:svg="http://www.w3.org/2000/svg"
-          xmlns:ns3="http://www.w3.org/1999/xhtml"
-          xmlns:mml="http://www.w3.org/1998/Math/MathML"
-          xmlns:scilab="http://www.scilab.org"
-          xmlns:db="http://docbook.org/ns/docbook">
-
-  <refnamediv>
-    <refname>qpipopt_mat</refname>
-    <refpurpose>Solves a linear quadratic problem.</refpurpose>
-  </refnamediv>
-
-
-<refsynopsisdiv>
-   <title>Calling Sequence</title>
-   <synopsis>
-   xopt = qpipopt_mat(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB)
-   x = qpipopt_mat(H,f)
-   x = qpipopt_mat(H,f,A,b)
-   x = qpipopt_mat(H,f,A,b,Aeq,beq)
-   x = qpipopt_mat(H,f,A,b,Aeq,beq,lb,ub)
-   [xopt,fopt,exitflag,output,lamda] = qpipopt_mat( ... )
-   
-   </synopsis>
-</refsynopsisdiv>
-
-<refsection>
-   <title>Parameters</title>
-   <variablelist>
-   <varlistentry><term>H :</term>
-      <listitem><para> a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.</para></listitem></varlistentry>
-   <varlistentry><term>f :</term>
-      <listitem><para> a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem</para></listitem></varlistentry>
-   <varlistentry><term>A :</term>
-      <listitem><para> a m x n matrix of doubles, represents the linear coefficients in the inequality constraints</para></listitem></varlistentry>
-   <varlistentry><term>b :</term>
-      <listitem><para> a column vector of doubles, represents the linear coefficients in the inequality constraints</para></listitem></varlistentry>
-   <varlistentry><term>Aeq :</term>
-      <listitem><para> a meq x n matrix of doubles, represents the linear coefficients in the equality constraints</para></listitem></varlistentry>
-   <varlistentry><term>beq :</term>
-      <listitem><para> a vector of doubles, represents the linear coefficients in the equality constraints</para></listitem></varlistentry>
-   <varlistentry><term>LB :</term>
-      <listitem><para> a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.</para></listitem></varlistentry>
-   <varlistentry><term>UB :</term>
-      <listitem><para> a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.</para></listitem></varlistentry>
-   <varlistentry><term>xopt :</term>
-      <listitem><para> a nx1 matrix of doubles, the computed solution of the optimization problem.</para></listitem></varlistentry>
-   <varlistentry><term>fopt :</term>
-      <listitem><para> a 1x1 matrix of doubles, the function value at x.</para></listitem></varlistentry>
-   <varlistentry><term>exitflag :</term>
-      <listitem><para> Integer identifying the reason the algorithm terminated.</para></listitem></varlistentry>
-   <varlistentry><term>output :</term>
-      <listitem><para> Structure containing information about the optimization.</para></listitem></varlistentry>
-   <varlistentry><term>lambda :</term>
-      <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).</para></listitem></varlistentry>
-   </variablelist>
-</refsection>
-
-<refsection>
-   <title>Description</title>
-   <para>
-Search the minimum of a constrained linear quadratic optimization problem specified by :
-find the minimum of f(x) such that
-   </para>
-   <para>
-<latex>
-\begin{eqnarray}
-&amp;\mbox{min}_{x}
-&amp; 1/2*x'*H*x + f'*x  \\
-&amp; \text{subject to} &amp; A.x \leq b \\
-&amp; &amp; Aeq.x \leq beq \\
-&amp; &amp; lb \leq x \leq ub \\
-\end{eqnarray}
-</latex>
-   </para>
-   <para>
-We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.
-   </para>
-   <para>
-</para>
-</refsection>
-
-<refsection>
-   <title>Examples</title>
-   <programlisting role="example"><![CDATA[
-//Find x in R^6 such that:
-
-Aeq= [1,-1,1,0,3,1;
--1,0,-3,-4,5,6;
-2,5,3,0,1,0];
-beq=[1; 2; 3];
-A= [0,1,0,1,2,-1;
--1,0,2,1,1,0];
-b = [-1; 2.5];
-lb=[-1000; -10000; 0; -1000; -1000; -1000];
-ub=[10000; 100; 1.5; 100; 100; 1000];
-//and minimize 0.5*x'*Q*x + p'*x with
-f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
-[xopt,fopt,exitflag,output,lambda]=qpipopt_mat(H,f,A,b,Aeq,beq,lb,ub)
-clear H f A b Aeq beq lb ub;
-
-   ]]></programlisting>
-</refsection>
-
-<refsection>
-   <title>Examples</title>
-   <programlisting role="example"><![CDATA[
-//Find the value of x that minimize following function
-// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2
-// Subject to:
-// x1 + x2 ≤ 2
-// –x1 + 2x2 ≤ 2
-// 2x1 + x2 ≤ 3
-// 0 ≤ x1, 0 ≤ x2.
-H = [1 -1; -1 2];
-f = [-2; -6];
-A = [1 1; -1 2; 2 1];
-b = [2; 2; 3];
-lb = [0; 0];
-ub = [%inf; %inf];
-[xopt,fopt,exitflag,output,lambda] = qpipopt_mat(H,f,A,b,[],[],lb,ub)
-
-   ]]></programlisting>
-</refsection>
-
-<refsection>
-   <title>Authors</title>
-   <simplelist type="vert">
-   <member>Keyur Joshi, Saikiran, Iswarya, Harpreet Singh</member>
-   </simplelist>
-</refsection>
-</refentry>
diff --git a/help/en_US/qpipoptmat.xml b/help/en_US/qpipoptmat.xml
index f3830f4..2ea714d 100644
--- a/help/en_US/qpipoptmat.xml
+++ b/help/en_US/qpipoptmat.xml
@@ -24,12 +24,12 @@
 <refsynopsisdiv>
    <title>Calling Sequence</title>
    <synopsis>
-   x = qpipoptmat(H,f)
-   x = qpipoptmat(H,f,A,b)
-   x = qpipoptmat(H,f,A,b,Aeq,beq)
-   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub)
-   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0)
-   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param)
+   xopt = qpipoptmat(H,f)
+   xopt = qpipoptmat(H,f,A,b)
+   xopt = qpipoptmat(H,f,A,b,Aeq,beq)
+   xopt = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub)
+   xopt = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0)
+   xopt = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param)
    [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... )
    
    </synopsis>
@@ -65,9 +65,9 @@
    <varlistentry><term>exitflag :</term>
       <listitem><para> Integer identifying the reason the algorithm terminated.</para></listitem></varlistentry>
    <varlistentry><term>output :</term>
-      <listitem><para> Structure containing information about the optimization.</para></listitem></varlistentry>
+      <listitem><para> Structure containing information about the optimization. Right now it contains number of iteration.</para></listitem></varlistentry>
    <varlistentry><term>lambda :</term>
-      <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).</para></listitem></varlistentry>
+      <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.</para></listitem></varlistentry>
    </variablelist>
 </refsection>
 
@@ -82,14 +82,14 @@ find the minimum of f(x) such that
 \begin{eqnarray}
 &amp;\mbox{min}_{x}
 &amp; 1/2*x'*H*x + f'*x  \\
-&amp; \text{subject to} &amp; A.x \leq b \\
-&amp; &amp; Aeq.x \leq beq \\
+&amp; \text{subject to} &amp; A*x \leq b \\
+&amp; &amp; Aeq*x = beq \\
 &amp; &amp; lb \leq x \leq ub \\
 \end{eqnarray}
 </latex>
    </para>
    <para>
-We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.
+We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++.
    </para>
    <para>
 </para>
@@ -98,30 +98,6 @@ We are calling IPOpt for solving the quadratic problem, IPOpt is a library writt
 <refsection>
    <title>Examples</title>
    <programlisting role="example"><![CDATA[
-//Find x in R^6 such that:
-
-Aeq= [1,-1,1,0,3,1;
--1,0,-3,-4,5,6;
-2,5,3,0,1,0];
-beq=[1; 2; 3];
-A= [0,1,0,1,2,-1;
--1,0,2,1,1,0];
-b = [-1; 2.5];
-lb=[-1000; -10000; 0; -1000; -1000; -1000];
-ub=[10000; 100; 1.5; 100; 100; 1000];
-x0 = repmat(0,6,1);
-param = list("MaxIter", 300, "CpuTime", 100);
-//and minimize 0.5*x'*Q*x + p'*x with
-f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
-[xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param)
-clear H f A b Aeq beq lb ub;
-
-   ]]></programlisting>
-</refsection>
-
-<refsection>
-   <title>Examples</title>
-   <programlisting role="example"><![CDATA[
 //Find the value of x that minimize following function
 // f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2
 // Subject to:
@@ -136,7 +112,29 @@ b = [2; 2; 3];
 lb = [0; 0];
 ub = [%inf; %inf];
 [xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub)
+// Press ENTER to continue
+
+   ]]></programlisting>
+</refsection>
 
+<refsection>
+   <title>Examples</title>
+   <programlisting role="example"><![CDATA[
+//Find x in R^6 such that:
+Aeq= [1,-1,1,0,3,1;
+-1,0,-3,-4,5,6;
+2,5,3,0,1,0];
+beq=[1; 2; 3];
+A= [0,1,0,1,2,-1;
+-1,0,2,1,1,0];
+b = [-1; 2.5];
+lb=[-1000; -10000; 0; -1000; -1000; -1000];
+ub=[10000; 100; 1.5; 100; 100; 1000];
+x0 = repmat(0,6,1);
+param = list("MaxIter", 300, "CpuTime", 100);
+//and minimize 0.5*x'*Q*x + p'*x with
+f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
+[xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param)
    ]]></programlisting>
 </refsection>
 
diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS
index 2aa9c2c..9b6386a 100644
--- a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS
+++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS
diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB
index 954ffd9..8f3ddaf 100644
--- a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB
+++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB
diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS b/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS
index d5a0fd6..d668ed6 100644
--- a/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS
+++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS
diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS b/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS
index 1fbf883..65379cd 100644
--- a/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS
+++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS
diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA b/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA
index 93aea58..b5697c6 100644
--- a/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA
+++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA
@@ -1,2 +1,2 @@
 JavaSearch 1.0
-TMAP bs=2048 rt=1 fl=-1 id1=1435 id2=1
+TMAP bs=2048 rt=1 fl=-1 id1=1439 id2=1
diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP b/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP
index 141985f..e2f089a 100644
--- a/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP
+++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP
diff --git a/help/en_US/scilab_en_US_help/_LaTeX_lsqlin.xml_1.png b/help/en_US/scilab_en_US_help/_LaTeX_lsqlin.xml_1.png
index d89b104..873dc47 100644
--- a/help/en_US/scilab_en_US_help/_LaTeX_lsqlin.xml_1.png
+++ b/help/en_US/scilab_en_US_help/_LaTeX_lsqlin.xml_1.png
diff --git a/help/en_US/scilab_en_US_help/_LaTeX_qpipoptmat.xml_1.png b/help/en_US/scilab_en_US_help/_LaTeX_qpipoptmat.xml_1.png
index b6e2743..7331197 100644
--- a/help/en_US/scilab_en_US_help/_LaTeX_qpipoptmat.xml_1.png
+++ b/help/en_US/scilab_en_US_help/_LaTeX_qpipoptmat.xml_1.png
diff --git a/help/en_US/scilab_en_US_help/_LaTeX_symphony.xml_1.png b/help/en_US/scilab_en_US_help/_LaTeX_symphony.xml_1.png
index 07dafd6..96b5161 100644
--- a/help/en_US/scilab_en_US_help/_LaTeX_symphony.xml_1.png
+++ b/help/en_US/scilab_en_US_help/_LaTeX_symphony.xml_1.png
diff --git a/help/en_US/scilab_en_US_help/_LaTeX_symphonymat.xml_1.png b/help/en_US/scilab_en_US_help/_LaTeX_symphonymat.xml_1.png
index 2e81ca1..94c5200 100644
--- a/help/en_US/scilab_en_US_help/_LaTeX_symphonymat.xml_1.png
+++ b/help/en_US/scilab_en_US_help/_LaTeX_symphonymat.xml_1.png
diff --git a/help/en_US/scilab_en_US_help/index.html b/help/en_US/scilab_en_US_help/index.html
index c942e96..03ce98c 100644
--- a/help/en_US/scilab_en_US_help/index.html
+++ b/help/en_US/scilab_en_US_help/index.html
@@ -50,12 +50,6 @@
 
 
 
-<li><a href="qpipopt_mat.html" class="refentry">qpipopt_mat</a> &#8212; <span class="refentry-description">Solves a linear quadratic problem.</span></li>
-
-
-
-
-
 <li><a href="qpipoptmat.html" class="refentry">qpipoptmat</a> &#8212; <span class="refentry-description">Solves a linear quadratic problem.</span></li>
 
 
@@ -68,12 +62,6 @@
 
 
 
-<li><a href="symphony_mat.html" class="refentry">symphony_mat</a> &#8212; <span class="refentry-description">Solves a mixed integer linear programming constrained optimization problem in intlinprog format.</span></li>
-
-
-
-
-
 <li><a href="symphonymat.html" class="refentry">symphonymat</a> &#8212; <span class="refentry-description">Solves a mixed integer linear programming constrained optimization problem in intlinprog format.</span></li>
 
 <li><a href="section_508f0b211d17ea6769714cc144e6b731.html" class="chapter">Symphony Native Functions</a>
diff --git a/help/en_US/scilab_en_US_help/jhelpmap.jhm b/help/en_US/scilab_en_US_help/jhelpmap.jhm
index f046f8a..0226c5e 100644
--- a/help/en_US/scilab_en_US_help/jhelpmap.jhm
+++ b/help/en_US/scilab_en_US_help/jhelpmap.jhm
@@ -6,10 +6,8 @@
 <mapID target="lsqlin" url="lsqlin.html"/>
 <mapID target="lsqnonneg" url="lsqnonneg.html"/>
 <mapID target="qpipopt" url="qpipopt.html"/>
-<mapID target="qpipopt_mat" url="qpipopt_mat.html"/>
 <mapID target="qpipoptmat" url="qpipoptmat.html"/>
 <mapID target="symphony" url="symphony.html"/>
-<mapID target="symphony_mat" url="symphony_mat.html"/>
 <mapID target="symphonymat" url="symphonymat.html"/>
 <mapID target="section_508f0b211d17ea6769714cc144e6b731" url="section_508f0b211d17ea6769714cc144e6b731.html"/>
 <mapID target="sym_addConstr" url="sym_addConstr.html"/>
diff --git a/help/en_US/scilab_en_US_help/jhelptoc.xml b/help/en_US/scilab_en_US_help/jhelptoc.xml
index 7722be3..f53e713 100644
--- a/help/en_US/scilab_en_US_help/jhelptoc.xml
+++ b/help/en_US/scilab_en_US_help/jhelptoc.xml
@@ -6,10 +6,8 @@
 <tocitem target="lsqlin" text="lsqlin"/>
 <tocitem target="lsqnonneg" text="lsqnonneg"/>
 <tocitem target="qpipopt" text="qpipopt"/>
-<tocitem target="qpipopt_mat" text="qpipopt_mat"/>
 <tocitem target="qpipoptmat" text="qpipoptmat"/>
 <tocitem target="symphony" text="symphony"/>
-<tocitem target="symphony_mat" text="symphony_mat"/>
 <tocitem target="symphonymat" text="symphonymat"/>
 <tocitem target="section_508f0b211d17ea6769714cc144e6b731" text="Symphony Native Functions">
 <tocitem target="sym_addConstr" text="sym_addConstr"/>
diff --git a/help/en_US/scilab_en_US_help/lsqlin.html b/help/en_US/scilab_en_US_help/lsqlin.html
index bf5a259..b371871 100644
--- a/help/en_US/scilab_en_US_help/lsqlin.html
+++ b/help/en_US/scilab_en_US_help/lsqlin.html
@@ -37,11 +37,11 @@
 
 
 <div class="refsynopsisdiv"><h3 class="title">Calling Sequence</h3>
-   <div class="synopsis"><pre><span class="default">x</span><span class="default"> = </span><span class="functionid">lsqlin</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">)</span>
-<span class="default">x</span><span class="default"> = </span><span class="functionid">lsqlin</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">)</span>
-<span class="default">x</span><span class="default"> = </span><span class="functionid">lsqlin</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">)</span>
-<span class="default">x</span><span class="default"> = </span><span class="functionid">lsqlin</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">,</span><span class="default">x0</span><span class="default">)</span>
-<span class="default">x</span><span class="default"> = </span><span class="functionid">lsqlin</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">,</span><span class="default">x0</span><span class="default">,</span><span class="default">param</span><span class="default">)</span>
+   <div class="synopsis"><pre><span class="default">xopt</span><span class="default"> = </span><span class="functionid">lsqlin</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">)</span>
+<span class="default">xopt</span><span class="default"> = </span><span class="functionid">lsqlin</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">)</span>
+<span class="default">xopt</span><span class="default"> = </span><span class="functionid">lsqlin</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">)</span>
+<span class="default">xopt</span><span class="default"> = </span><span class="functionid">lsqlin</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">,</span><span class="default">x0</span><span class="default">)</span>
+<span class="default">xopt</span><span class="default"> = </span><span class="functionid">lsqlin</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">,</span><span class="default">x0</span><span class="default">,</span><span class="default">param</span><span class="default">)</span>
 <span class="default">[</span><span class="default">xopt</span><span class="default">,</span><span class="default">resnorm</span><span class="default">,</span><span class="default">residual</span><span class="default">,</span><span class="default">exitflag</span><span class="default">,</span><span class="default">output</span><span class="default">,</span><span class="default">lambda</span><span class="default">] = </span><span class="functionid">lsqlin</span><span class="default">( ... )</span></pre></div></div>
 
 <div class="refsection"><h3 class="title">Parameters</h3>
@@ -74,14 +74,14 @@
    <dt><span class="term">exitflag :</span>
       <dd><p class="para">Integer identifying the reason the algorithm terminated.</p></dd></dt>
    <dt><span class="term">output :</span>
-      <dd><p class="para">Structure containing information about the optimization.</p></dd></dt>
+      <dd><p class="para">Structure containing information about the optimization. Right now it contains number of iteration.</p></dd></dt>
    <dt><span class="term">lambda :</span>
-      <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).</p></dd></dt></dl></div>
+      <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.</p></dd></dt></dl></div>
 
 <div class="refsection"><h3 class="title">Description</h3>
    <p class="para">Search the minimum of a constrained linear least square problem specified by :</p>
    <p class="para"><span><img src='./_LaTeX_lsqlin.xml_1.png' style='position:relative;top:41px;width:234px;height:90px'/></span></p>
-   <p class="para">We are calling IPOpt for solving the linear least square problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.</p>
+   <p class="para">We are calling IPOpt for solving the linear least square problem, IPOpt is a library written in C++.</p>
    <p class="para"></p></div>
 
 <div class="refsection"><h3 class="title">Examples</h3>
@@ -102,10 +102,12 @@
 <span class="scilabid">b</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">0.5251</span>
 <span class="scilabnumber">0.2026</span>
 <span class="scilabnumber">0.6721</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabopenclose">[</span><span class="scilabid">xopt</span><span class="scilabdefault">,</span><span class="scilabid">resnorm</span><span class="scilabdefault">,</span><span class="scilabid">residual</span><span class="scilabdefault">,</span><span class="scilabid">exitflag</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabdefault">,</span><span class="scilabid">lambda</span><span class="scilabopenclose">]</span> <span class="scilaboperator">=</span> <span class="scilabid">lsqlin</span><span class="scilabopenclose">(</span><span class="scilabid">C</span><span class="scilabdefault">,</span><span class="scilabid">d</span><span class="scilabdefault">,</span><span class="scilabid">A</span><span class="scilabdefault">,</span><span class="scilabid">b</span><span class="scilabopenclose">)</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
+<span class="scilabopenclose">[</span><span class="scilabid">xopt</span><span class="scilabdefault">,</span><span class="scilabid">resnorm</span><span class="scilabdefault">,</span><span class="scilabid">residual</span><span class="scilabdefault">,</span><span class="scilabid">exitflag</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabdefault">,</span><span class="scilabid">lambda</span><span class="scilabopenclose">]</span> <span class="scilaboperator">=</span> <span class="scilabid">lsqlin</span><span class="scilabopenclose">(</span><span class="scilabid">C</span><span class="scilabdefault">,</span><span class="scilabid">d</span><span class="scilabdefault">,</span><span class="scilabid">A</span><span class="scilabdefault">,</span><span class="scilabid">b</span><span class="scilabopenclose">)</span>
+<span class="scilabcomment">// Press ENTER to continue</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
 
 <div class="refsection"><h3 class="title">Examples</h3>
-   <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabid">C</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">0.9501</span>    <span class="scilabnumber">0.7620</span>    <span class="scilabnumber">0.6153</span>    <span class="scilabnumber">0.4057</span>
+   <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabcomment">//A basic example for equality, inequality and bounds</span>
+<span class="scilabid">C</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">0.9501</span>    <span class="scilabnumber">0.7620</span>    <span class="scilabnumber">0.6153</span>    <span class="scilabnumber">0.4057</span>
 <span class="scilabnumber">0.2311</span>    <span class="scilabnumber">0.4564</span>    <span class="scilabnumber">0.7919</span>    <span class="scilabnumber">0.9354</span>
 <span class="scilabnumber">0.6068</span>    <span class="scilabnumber">0.0185</span>    <span class="scilabnumber">0.9218</span>    <span class="scilabnumber">0.9169</span>
 <span class="scilabnumber">0.4859</span>    <span class="scilabnumber">0.8214</span>    <span class="scilabnumber">0.7382</span>    <span class="scilabnumber">0.4102</span>
diff --git a/help/en_US/scilab_en_US_help/lsqnonneg.html b/help/en_US/scilab_en_US_help/lsqnonneg.html
index 4f2f661..40139a0 100644
--- a/help/en_US/scilab_en_US_help/lsqnonneg.html
+++ b/help/en_US/scilab_en_US_help/lsqnonneg.html
@@ -37,8 +37,8 @@
 
 
 <div class="refsynopsisdiv"><h3 class="title">Calling Sequence</h3>
-   <div class="synopsis"><pre><span class="default">x</span><span class="default"> = </span><span class="functionid">lsqnonneg</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">)</span>
-<span class="default">x</span><span class="default"> = </span><span class="functionid">lsqnonneg</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">param</span><span class="default">)</span>
+   <div class="synopsis"><pre><span class="default">xopt</span><span class="default"> = </span><span class="functionid">lsqnonneg</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">)</span>
+<span class="default">xopt</span><span class="default"> = </span><span class="functionid">lsqnonneg</span><span class="default">(</span><span class="default">C</span><span class="default">,</span><span class="default">d</span><span class="default">,</span><span class="default">param</span><span class="default">)</span>
 <span class="default">[</span><span class="default">xopt</span><span class="default">,</span><span class="default">resnorm</span><span class="default">,</span><span class="default">residual</span><span class="default">,</span><span class="default">exitflag</span><span class="default">,</span><span class="default">output</span><span class="default">,</span><span class="default">lambda</span><span class="default">] = </span><span class="functionid">lsqnonneg</span><span class="default">( ... )</span></pre></div></div>
 
 <div class="refsection"><h3 class="title">Parameters</h3>
@@ -55,18 +55,18 @@
    <dt><span class="term">exitflag :</span>
       <dd><p class="para">Integer identifying the reason the algorithm terminated.</p></dd></dt>
    <dt><span class="term">output :</span>
-      <dd><p class="para">Structure containing information about the optimization.</p></dd></dt>
+      <dd><p class="para">Structure containing information about the optimization. Right now it contains number of iteration.</p></dd></dt>
    <dt><span class="term">lambda :</span>
-      <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).</p></dd></dt></dl></div>
+      <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.</p></dd></dt></dl></div>
 
 <div class="refsection"><h3 class="title">Description</h3>
    <p class="para">Solves nonnegative least-squares curve fitting problems specified by :</p>
    <p class="para"><span><img src='./_LaTeX_lsqnonneg.xml_1.png' style='position:relative;top:19px;width:197px;height:46px'/></span></p>
-   <p class="para">We are calling IPOpt for solving the nonnegative least-squares curve fitting problems, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.</p>
+   <p class="para">We are calling IPOpt for solving the nonnegative least-squares curve fitting problems, IPOpt is a library written in C++.</p>
    <p class="para"></p></div>
 
 <div class="refsection"><h3 class="title">Examples</h3>
-   <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabid">A</span> <span class="scilabid">basic</span> <span class="scilabid">lsqnonneg</span> <span class="scilabid">problem</span>
+   <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabcomment">// A basic lsqnonneg problem</span>
 <span class="scilabid">C</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span>
 <span class="scilabnumber">0.0372</span>    <span class="scilabnumber">0.2869</span>
 <span class="scilabnumber">0.6861</span>    <span class="scilabnumber">0.7071</span>
diff --git a/help/en_US/scilab_en_US_help/qpipopt.html b/help/en_US/scilab_en_US_help/qpipopt.html
index 7588c1d..7cc0560 100644
--- a/help/en_US/scilab_en_US_help/qpipopt.html
+++ b/help/en_US/scilab_en_US_help/qpipopt.html
@@ -20,7 +20,7 @@
 
       </td>
       <td width="30%" class="next">
-      	<span class="next"><a href="qpipopt_mat.html">qpipopt_mat &gt;&gt;</a></span>
+      	<span class="next"><a href="qpipoptmat.html">qpipoptmat &gt;&gt;</a></span>
 
       </td>
     </tr></table>
@@ -72,15 +72,15 @@
    <dt><span class="term">exitflag :</span>
       <dd><p class="para">Integer identifying the reason the algorithm terminated.</p></dd></dt>
    <dt><span class="term">output :</span>
-      <dd><p class="para">Structure containing information about the optimization.</p></dd></dt>
+      <dd><p class="para">Structure containing information about the optimization. Right now it contains number of iteration.</p></dd></dt>
    <dt><span class="term">lambda :</span>
-      <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).</p></dd></dt></dl></div>
+      <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.</p></dd></dt></dl></div>
 
 <div class="refsection"><h3 class="title">Description</h3>
    <p class="para">Search the minimum of a constrained linear quadratic optimization problem specified by :
 find the minimum of f(x) such that</p>
    <p class="para"><span><img src='./_LaTeX_qpipopt.xml_1.png' style='position:relative;top:31px;width:293px;height:70px'/></span></p>
-   <p class="para">We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.</p>
+   <p class="para">We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++.</p>
    <p class="para"></p></div>
 
 <div class="refsection"><h3 class="title">Examples</h3>
@@ -100,7 +100,8 @@ find the minimum of f(x) such that</p>
 <span class="scilabid">nbCon</span> <span class="scilaboperator">=</span> <span class="scilabnumber">5</span><span class="scilabdefault">;</span>
 <span class="scilabid">x0</span> <span class="scilaboperator">=</span> <a class="scilabmacro" href="scilab://repmat">repmat</a><span class="scilabopenclose">(</span><span class="scilabnumber">0</span><span class="scilabdefault">,</span><span class="scilabid">nbVar</span><span class="scilabdefault">,</span><span class="scilabnumber">1</span><span class="scilabopenclose">)</span><span class="scilabdefault">;</span>
 <span class="scilabid">param</span> <span class="scilaboperator">=</span> <a class="scilabcommand" href="scilab://list">list</a><span class="scilabopenclose">(</span><span class="scilabstring">&#0034;</span><span class="scilabstring">MaxIter</span><span class="scilabstring">&#0034;</span><span class="scilabdefault">,</span> <span class="scilabnumber">300</span><span class="scilabdefault">,</span> <span class="scilabstring">&#0034;</span><span class="scilabstring">CpuTime</span><span class="scilabstring">&#0034;</span><span class="scilabdefault">,</span> <span class="scilabnumber">100</span><span class="scilabopenclose">)</span><span class="scilabdefault">;</span>
-<span class="scilabopenclose">[</span><span class="scilabid">xopt</span><span class="scilabdefault">,</span><span class="scilabid">fopt</span><span class="scilabdefault">,</span><span class="scilabid">exitflag</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabdefault">,</span><span class="scilabid">lambda</span><span class="scilabopenclose">]</span><span class="scilaboperator">=</span><span class="scilabid">qpipopt</span><span class="scilabopenclose">(</span><span class="scilabid">nbVar</span><span class="scilabdefault">,</span><span class="scilabid">nbCon</span><span class="scilabdefault">,</span><span class="scilabid">Q</span><span class="scilabdefault">,</span><span class="scilabid">p</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabdefault">,</span><span class="scilabid">conMatrix</span><span class="scilabdefault">,</span><span class="scilabid">conLB</span><span class="scilabdefault">,</span><span class="scilabid">conUB</span><span class="scilabdefault">,</span><span class="scilabid">x0</span><span class="scilabdefault">,</span><span class="scilabid">param</span><span class="scilabopenclose">)</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
+<span class="scilabopenclose">[</span><span class="scilabid">xopt</span><span class="scilabdefault">,</span><span class="scilabid">fopt</span><span class="scilabdefault">,</span><span class="scilabid">exitflag</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabdefault">,</span><span class="scilabid">lambda</span><span class="scilabopenclose">]</span><span class="scilaboperator">=</span><span class="scilabid">qpipopt</span><span class="scilabopenclose">(</span><span class="scilabid">nbVar</span><span class="scilabdefault">,</span><span class="scilabid">nbCon</span><span class="scilabdefault">,</span><span class="scilabid">Q</span><span class="scilabdefault">,</span><span class="scilabid">p</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabdefault">,</span><span class="scilabid">conMatrix</span><span class="scilabdefault">,</span><span class="scilabid">conLB</span><span class="scilabdefault">,</span><span class="scilabid">conUB</span><span class="scilabdefault">,</span><span class="scilabid">x0</span><span class="scilabdefault">,</span><span class="scilabid">param</span><span class="scilabopenclose">)</span>
+<span class="scilabcomment">// Press ENTER to continue</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
 
 <div class="refsection"><h3 class="title">Examples</h3>
    <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabcomment">//Find the value of x that minimize following function</span>
@@ -138,7 +139,7 @@ find the minimum of f(x) such that</p>
 
       </td>
       <td width="30%" class="next">
-      	<span class="next"><a href="qpipopt_mat.html">qpipopt_mat &gt;&gt;</a></span>
+      	<span class="next"><a href="qpipoptmat.html">qpipoptmat &gt;&gt;</a></span>
 
       </td>
     </tr></table>
diff --git a/help/en_US/scilab_en_US_help/qpipoptmat.html b/help/en_US/scilab_en_US_help/qpipoptmat.html
index e1d301a..8b81cac 100644
--- a/help/en_US/scilab_en_US_help/qpipoptmat.html
+++ b/help/en_US/scilab_en_US_help/qpipoptmat.html
@@ -12,7 +12,7 @@
     <div class="manualnavbar">
     <table width="100%"><tr>
       <td width="30%">
-    	<span class="previous"><a href="qpipopt_mat.html">&lt;&lt; qpipopt_mat</a></span>
+    	<span class="previous"><a href="qpipopt.html">&lt;&lt; qpipopt</a></span>
 
       </td>
       <td width="40%" class="center">
@@ -37,12 +37,12 @@
 
 
 <div class="refsynopsisdiv"><h3 class="title">Calling Sequence</h3>
-   <div class="synopsis"><pre><span class="default">x</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">)</span>
-<span class="default">x</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">)</span>
-<span class="default">x</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">)</span>
-<span class="default">x</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">)</span>
-<span class="default">x</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">,</span><span class="default">x0</span><span class="default">)</span>
-<span class="default">x</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">,</span><span class="default">x0</span><span class="default">,</span><span class="default">param</span><span class="default">)</span>
+   <div class="synopsis"><pre><span class="default">xopt</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">)</span>
+<span class="default">xopt</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">)</span>
+<span class="default">xopt</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">)</span>
+<span class="default">xopt</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">)</span>
+<span class="default">xopt</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">,</span><span class="default">x0</span><span class="default">)</span>
+<span class="default">xopt</span><span class="default"> = </span><span class="functionid">qpipoptmat</span><span class="default">(</span><span class="default">H</span><span class="default">,</span><span class="default">f</span><span class="default">,</span><span class="default">A</span><span class="default">,</span><span class="default">b</span><span class="default">,</span><span class="default">Aeq</span><span class="default">,</span><span class="default">beq</span><span class="default">,</span><span class="default">lb</span><span class="default">,</span><span class="default">ub</span><span class="default">,</span><span class="default">x0</span><span class="default">,</span><span class="default">param</span><span class="default">)</span>
 <span class="default">[</span><span class="default">xopt</span><span class="default">,</span><span class="default">fopt</span><span class="default">,</span><span class="default">exitflag</span><span class="default">,</span><span class="default">output</span><span class="default">,</span><span class="default">lamda</span><span class="default">] = </span><span class="functionid">qpipoptmat</span><span class="default">( ... )</span></pre></div></div>
 
 <div class="refsection"><h3 class="title">Parameters</h3>
@@ -73,20 +73,36 @@
    <dt><span class="term">exitflag :</span>
       <dd><p class="para">Integer identifying the reason the algorithm terminated.</p></dd></dt>
    <dt><span class="term">output :</span>
-      <dd><p class="para">Structure containing information about the optimization.</p></dd></dt>
+      <dd><p class="para">Structure containing information about the optimization. Right now it contains number of iteration.</p></dd></dt>
    <dt><span class="term">lambda :</span>
-      <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).</p></dd></dt></dl></div>
+      <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.</p></dd></dt></dl></div>
 
 <div class="refsection"><h3 class="title">Description</h3>
    <p class="para">Search the minimum of a constrained linear quadratic optimization problem specified by :
 find the minimum of f(x) such that</p>
    <p class="para"><span><img src='./_LaTeX_qpipoptmat.xml_1.png' style='position:relative;top:40px;width:284px;height:88px'/></span></p>
-   <p class="para">We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.</p>
+   <p class="para">We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++.</p>
    <p class="para"></p></div>
 
 <div class="refsection"><h3 class="title">Examples</h3>
-   <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabcomment">//Find x in R^6 such that:</span>
+   <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabcomment">//Find the value of x that minimize following function</span>
+<span class="scilabcomment">// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2</span>
+<span class="scilabcomment">// Subject to:</span>
+<span class="scilabcomment">// x1 + x2 ≤ 2</span>
+<span class="scilabcomment">// –x1 + 2x2 ≤ 2</span>
+<span class="scilabcomment">// 2x1 + x2 ≤ 3</span>
+<span class="scilabcomment">// 0 ≤ x1, 0 ≤ x2.</span>
+<span class="scilabid">H</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">1</span> <span class="scilaboperator">-</span><span class="scilabnumber">1</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">1</span> <span class="scilabnumber">2</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">f</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilaboperator">-</span><span class="scilabnumber">2</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">6</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">A</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">1</span> <span class="scilabnumber">1</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">1</span> <span class="scilabnumber">2</span><span class="scilabdefault">;</span> <span class="scilabnumber">2</span> <span class="scilabnumber">1</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">b</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">2</span><span class="scilabdefault">;</span> <span class="scilabnumber">2</span><span class="scilabdefault">;</span> <span class="scilabnumber">3</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">lb</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">0</span><span class="scilabdefault">;</span> <span class="scilabnumber">0</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">ub</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabconstants">%inf</span><span class="scilabdefault">;</span> <span class="scilabconstants">%inf</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabopenclose">[</span><span class="scilabid">xopt</span><span class="scilabdefault">,</span><span class="scilabid">fopt</span><span class="scilabdefault">,</span><span class="scilabid">exitflag</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabdefault">,</span><span class="scilabid">lambda</span><span class="scilabopenclose">]</span> <span class="scilaboperator">=</span> <span class="scilabid">qpipoptmat</span><span class="scilabopenclose">(</span><span class="scilabid">H</span><span class="scilabdefault">,</span><span class="scilabid">f</span><span class="scilabdefault">,</span><span class="scilabid">A</span><span class="scilabdefault">,</span><span class="scilabid">b</span><span class="scilabdefault">,</span><span class="scilabopenclose">[</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabopenclose">[</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabopenclose">)</span>
+<span class="scilabcomment">// Press ENTER to continue</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
 
+<div class="refsection"><h3 class="title">Examples</h3>
+   <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabcomment">//Find x in R^6 such that:</span>
 <span class="scilabid">Aeq</span><span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilaboperator">-</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilabnumber">0</span><span class="scilabdefault">,</span><span class="scilabnumber">3</span><span class="scilabdefault">,</span><span class="scilabnumber">1</span><span class="scilabdefault">;</span>
 <span class="scilaboperator">-</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilabnumber">0</span><span class="scilabdefault">,</span><span class="scilaboperator">-</span><span class="scilabnumber">3</span><span class="scilabdefault">,</span><span class="scilaboperator">-</span><span class="scilabnumber">4</span><span class="scilabdefault">,</span><span class="scilabnumber">5</span><span class="scilabdefault">,</span><span class="scilabnumber">6</span><span class="scilabdefault">;</span>
 <span class="scilabnumber">2</span><span class="scilabdefault">,</span><span class="scilabnumber">5</span><span class="scilabdefault">,</span><span class="scilabnumber">3</span><span class="scilabdefault">,</span><span class="scilabnumber">0</span><span class="scilabdefault">,</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilabnumber">0</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
@@ -100,24 +116,7 @@ find the minimum of f(x) such that</p>
 <span class="scilabid">param</span> <span class="scilaboperator">=</span> <a class="scilabcommand" href="scilab://list">list</a><span class="scilabopenclose">(</span><span class="scilabstring">&#0034;</span><span class="scilabstring">MaxIter</span><span class="scilabstring">&#0034;</span><span class="scilabdefault">,</span> <span class="scilabnumber">300</span><span class="scilabdefault">,</span> <span class="scilabstring">&#0034;</span><span class="scilabstring">CpuTime</span><span class="scilabstring">&#0034;</span><span class="scilabdefault">,</span> <span class="scilabnumber">100</span><span class="scilabopenclose">)</span><span class="scilabdefault">;</span>
 <span class="scilabcomment">//and minimize 0.5*x</span><span class="scilabcomment">&#0039;</span><span class="scilabcomment">*Q*x + p</span><span class="scilabcomment">&#0039;</span><span class="scilabcomment">*x with</span>
 <span class="scilabid">f</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilabnumber">1</span><span class="scilabdefault">;</span> <span class="scilabnumber">2</span><span class="scilabdefault">;</span> <span class="scilabnumber">3</span><span class="scilabdefault">;</span> <span class="scilabnumber">4</span><span class="scilabdefault">;</span> <span class="scilabnumber">5</span><span class="scilabdefault">;</span> <span class="scilabnumber">6</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span> <span class="scilabid">H</span><span class="scilaboperator">=</span><a class="scilabcommand" href="scilab://eye">eye</a><span class="scilabopenclose">(</span><span class="scilabnumber">6</span><span class="scilabdefault">,</span><span class="scilabnumber">6</span><span class="scilabopenclose">)</span><span class="scilabdefault">;</span>
-<span class="scilabopenclose">[</span><span class="scilabid">xopt</span><span class="scilabdefault">,</span><span class="scilabid">fopt</span><span class="scilabdefault">,</span><span class="scilabid">exitflag</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabdefault">,</span><span class="scilabid">lambda</span><span class="scilabopenclose">]</span><span class="scilaboperator">=</span><span class="scilabid">qpipoptmat</span><span class="scilabopenclose">(</span><span class="scilabid">H</span><span class="scilabdefault">,</span><span class="scilabid">f</span><span class="scilabdefault">,</span><span class="scilabid">A</span><span class="scilabdefault">,</span><span class="scilabid">b</span><span class="scilabdefault">,</span><span class="scilabid">Aeq</span><span class="scilabdefault">,</span><span class="scilabid">beq</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabdefault">,</span><span class="scilabopenclose">[</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabid">param</span><span class="scilabopenclose">)</span>
-<span class="scilabid">clear</span> <span class="scilabid">H</span> <span class="scilabid">f</span> <span class="scilabid">A</span> <span class="scilabid">b</span> <span class="scilabid">Aeq</span> <span class="scilabid">beq</span> <span class="scilabid">lb</span> <span class="scilabid">ub</span><span class="scilabdefault">;</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
-
-<div class="refsection"><h3 class="title">Examples</h3>
-   <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabcomment">//Find the value of x that minimize following function</span>
-<span class="scilabcomment">// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2</span>
-<span class="scilabcomment">// Subject to:</span>
-<span class="scilabcomment">// x1 + x2 ≤ 2</span>
-<span class="scilabcomment">// –x1 + 2x2 ≤ 2</span>
-<span class="scilabcomment">// 2x1 + x2 ≤ 3</span>
-<span class="scilabcomment">// 0 ≤ x1, 0 ≤ x2.</span>
-<span class="scilabid">H</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">1</span> <span class="scilaboperator">-</span><span class="scilabnumber">1</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">1</span> <span class="scilabnumber">2</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">f</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilaboperator">-</span><span class="scilabnumber">2</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">6</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">A</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">1</span> <span class="scilabnumber">1</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">1</span> <span class="scilabnumber">2</span><span class="scilabdefault">;</span> <span class="scilabnumber">2</span> <span class="scilabnumber">1</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">b</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">2</span><span class="scilabdefault">;</span> <span class="scilabnumber">2</span><span class="scilabdefault">;</span> <span class="scilabnumber">3</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">lb</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">0</span><span class="scilabdefault">;</span> <span class="scilabnumber">0</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">ub</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabconstants">%inf</span><span class="scilabdefault">;</span> <span class="scilabconstants">%inf</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabopenclose">[</span><span class="scilabid">xopt</span><span class="scilabdefault">,</span><span class="scilabid">fopt</span><span class="scilabdefault">,</span><span class="scilabid">exitflag</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabdefault">,</span><span class="scilabid">lambda</span><span class="scilabopenclose">]</span> <span class="scilaboperator">=</span> <span class="scilabid">qpipoptmat</span><span class="scilabopenclose">(</span><span class="scilabid">H</span><span class="scilabdefault">,</span><span class="scilabid">f</span><span class="scilabdefault">,</span><span class="scilabid">A</span><span class="scilabdefault">,</span><span class="scilabid">b</span><span class="scilabdefault">,</span><span class="scilabopenclose">[</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabopenclose">[</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabopenclose">)</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
+<span class="scilabopenclose">[</span><span class="scilabid">xopt</span><span class="scilabdefault">,</span><span class="scilabid">fopt</span><span class="scilabdefault">,</span><span class="scilabid">exitflag</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabdefault">,</span><span class="scilabid">lambda</span><span class="scilabopenclose">]</span><span class="scilaboperator">=</span><span class="scilabid">qpipoptmat</span><span class="scilabopenclose">(</span><span class="scilabid">H</span><span class="scilabdefault">,</span><span class="scilabid">f</span><span class="scilabdefault">,</span><span class="scilabid">A</span><span class="scilabdefault">,</span><span class="scilabid">b</span><span class="scilabdefault">,</span><span class="scilabid">Aeq</span><span class="scilabdefault">,</span><span class="scilabid">beq</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabdefault">,</span><span class="scilabopenclose">[</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabid">param</span><span class="scilabopenclose">)</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
 
 <div class="refsection"><h3 class="title">Authors</h3>
    <ul class="itemizedlist"><li class="member">Keyur Joshi, Saikiran, Iswarya, Harpreet Singh</li></ul></div>
@@ -128,7 +127,7 @@ find the minimum of f(x) such that</p>
     <tr><td colspan="3" class="next"><a href="http://bugzilla.scilab.org/enter_bug.cgi?product=Scilab%20software&component=Documentation%20pages" class="ulink">Report an issue</a></td></tr>
 <tr>
       <td width="30%">
-    	<span class="previous"><a href="qpipopt_mat.html">&lt;&lt; qpipopt_mat</a></span>
+    	<span class="previous"><a href="qpipopt.html">&lt;&lt; qpipopt</a></span>
 
       </td>
       <td width="40%" class="center">
diff --git a/help/en_US/scilab_en_US_help/section_19f4f1e5726c01d683e8b82be0a7e910.html b/help/en_US/scilab_en_US_help/section_19f4f1e5726c01d683e8b82be0a7e910.html
index 7219261..a79bad0 100644
--- a/help/en_US/scilab_en_US_help/section_19f4f1e5726c01d683e8b82be0a7e910.html
+++ b/help/en_US/scilab_en_US_help/section_19f4f1e5726c01d683e8b82be0a7e910.html
@@ -49,12 +49,6 @@
 
 
 
-<li><a href="qpipopt_mat.html" class="refentry">qpipopt_mat</a> &#8212; <span class="refentry-description">Solves a linear quadratic problem.</span></li>
-
-
-
-
-
 <li><a href="qpipoptmat.html" class="refentry">qpipoptmat</a> &#8212; <span class="refentry-description">Solves a linear quadratic problem.</span></li>
 
 
@@ -67,12 +61,6 @@
 
 
 
-<li><a href="symphony_mat.html" class="refentry">symphony_mat</a> &#8212; <span class="refentry-description">Solves a mixed integer linear programming constrained optimization problem in intlinprog format.</span></li>
-
-
-
-
-
 <li><a href="symphonymat.html" class="refentry">symphonymat</a> &#8212; <span class="refentry-description">Solves a mixed integer linear programming constrained optimization problem in intlinprog format.</span></li>
 
 <li><a href="section_508f0b211d17ea6769714cc144e6b731.html" class="chapter">Symphony Native Functions</a>
diff --git a/help/en_US/scilab_en_US_help/symphony.html b/help/en_US/scilab_en_US_help/symphony.html
index 14e9118..9b2bebe 100644
--- a/help/en_US/scilab_en_US_help/symphony.html
+++ b/help/en_US/scilab_en_US_help/symphony.html
@@ -20,7 +20,7 @@
 
       </td>
       <td width="30%" class="next">
-      	<span class="next"><a href="symphony_mat.html">symphony_mat &gt;&gt;</a></span>
+      	<span class="next"><a href="symphonymat.html">symphonymat &gt;&gt;</a></span>
 
       </td>
     </tr></table>
@@ -72,13 +72,13 @@
    <dt><span class="term">status :</span>
       <dd><p class="para">status flag from symphony.</p></dd></dt>
    <dt><span class="term">output :</span>
-      <dd><p class="para">The output data structure contains detailed informations about the optimization process.</p></dd></dt></dl></div>
+      <dd><p class="para">The output data structure contains detailed informations about the optimization process. Right now it contains number of iteration.</p></dd></dt></dl></div>
 
 <div class="refsection"><h3 class="title">Description</h3>
    <p class="para">Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
 find the minimum or maximum of f(x) such that</p>
-   <p class="para"><span><img src='./_LaTeX_symphony.xml_1.png' style='position:relative;top:31px;width:293px;height:70px'/></span></p>
-   <p class="para">We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.</p>
+   <p class="para"><span><img src='./_LaTeX_symphony.xml_1.png' style='position:relative;top:41px;width:295px;height:90px'/></span></p>
+   <p class="para">We are calling SYMPHONY written in C by gateway files for the actual computation.</p>
    <p class="para"></p></div>
 
 <div class="refsection"><h3 class="title">Examples</h3>
@@ -102,7 +102,8 @@ find the minimum or maximum of f(x) such that</p>
 <span class="scilabid">xopt</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">1</span> <span class="scilabnumber">1</span> <span class="scilabnumber">0</span> <span class="scilabnumber">1</span> <span class="scilabnumber">7.25</span> <span class="scilabnumber">0</span> <span class="scilabnumber">0.25</span> <span class="scilabnumber">3.5</span><span class="scilabopenclose">]</span>
 <span class="scilabid">fopt</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">8495</span><span class="scilabopenclose">]</span>
 <span class="scilabcomment">// Calling Symphony</span>
-<span class="scilabopenclose">[</span><span class="scilabid">x</span><span class="scilabdefault">,</span><span class="scilabid">f</span><span class="scilabdefault">,</span><span class="scilabid">status</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabopenclose">]</span> <span class="scilaboperator">=</span> <span class="scilabid">symphony</span><span class="scilabopenclose">(</span><span class="scilabnumber">8</span><span class="scilabdefault">,</span><span class="scilabnumber">3</span><span class="scilabdefault">,</span><span class="scilabid">c</span><span class="scilabdefault">,</span><span class="scilabid">isInt</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabdefault">,</span><span class="scilabid">conMatrix</span><span class="scilabdefault">,</span><span class="scilabid">conlb</span><span class="scilabdefault">,</span><span class="scilabid">conub</span><span class="scilabdefault">,</span><span class="scilabnumber">1</span><span class="scilabopenclose">)</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
+<span class="scilabopenclose">[</span><span class="scilabid">x</span><span class="scilabdefault">,</span><span class="scilabid">f</span><span class="scilabdefault">,</span><span class="scilabid">status</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabopenclose">]</span> <span class="scilaboperator">=</span> <span class="scilabid">symphony</span><span class="scilabopenclose">(</span><span class="scilabnumber">8</span><span class="scilabdefault">,</span><span class="scilabnumber">3</span><span class="scilabdefault">,</span><span class="scilabid">c</span><span class="scilabdefault">,</span><span class="scilabid">isInt</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabdefault">,</span><span class="scilabid">conMatrix</span><span class="scilabdefault">,</span><span class="scilabid">conlb</span><span class="scilabdefault">,</span><span class="scilabid">conub</span><span class="scilabdefault">,</span><span class="scilabnumber">1</span><span class="scilabopenclose">)</span>
+<span class="scilabcomment">// Press ENTER to continue</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
 
 <div class="refsection"><h3 class="title">Examples</h3>
    <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabcomment">// An advanced case where we set some options in symphony</span>
@@ -186,7 +187,7 @@ find the minimum or maximum of f(x) such that</p>
 <span class="scilabcomment">// Optimal value</span>
 <span class="scilabid">fopt</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span> <span class="scilabnumber">24381</span> <span class="scilabopenclose">]</span>
 <span class="scilabcomment">// Calling Symphony</span>
-<span class="scilabopenclose">[</span><span class="scilabid">x</span><span class="scilabdefault">,</span><span class="scilabid">f</span><span class="scilabdefault">,</span><span class="scilabid">status</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabopenclose">]</span> <span class="scilaboperator">=</span> <span class="scilabid">symphony</span><span class="scilabopenclose">(</span><span class="scilabid">nbVar</span><span class="scilabdefault">,</span><span class="scilabid">nbCon</span><span class="scilabdefault">,</span><span class="scilabid">p</span><span class="scilabdefault">,</span><span class="scilabid">isInt</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabdefault">,</span><span class="scilabid">conMatrix</span><span class="scilabdefault">,</span><span class="scilabid">conLB</span><span class="scilabdefault">,</span><span class="scilabid">conUB</span><span class="scilabdefault">,</span><span class="scilaboperator">-</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilabid">options</span><span class="scilabopenclose">)</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
+<span class="scilabopenclose">[</span><span class="scilabid">x</span><span class="scilabdefault">,</span><span class="scilabid">f</span><span class="scilabdefault">,</span><span class="scilabid">status</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabopenclose">]</span> <span class="scilaboperator">=</span> <span class="scilabid">symphony</span><span class="scilabopenclose">(</span><span class="scilabid">nbVar</span><span class="scilabdefault">,</span><span class="scilabid">nbCon</span><span class="scilabdefault">,</span><span class="scilabid">p</span><span class="scilabdefault">,</span><span class="scilabid">isInt</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabdefault">,</span><span class="scilabid">conMatrix</span><span class="scilabdefault">,</span><span class="scilabid">conLB</span><span class="scilabdefault">,</span><span class="scilabid">conUB</span><span class="scilabdefault">,</span><span class="scilaboperator">-</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilabid">options</span><span class="scilabopenclose">)</span><span class="scilabdefault">;</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
 
 <div class="refsection"><h3 class="title">Authors</h3>
    <ul class="itemizedlist"><li class="member">Keyur Joshi, Saikiran, Iswarya, Harpreet Singh</li></ul></div>
@@ -205,7 +206,7 @@ find the minimum or maximum of f(x) such that</p>
 
       </td>
       <td width="30%" class="next">
-      	<span class="next"><a href="symphony_mat.html">symphony_mat &gt;&gt;</a></span>
+      	<span class="next"><a href="symphonymat.html">symphonymat &gt;&gt;</a></span>
 
       </td>
     </tr></table>
diff --git a/help/en_US/scilab_en_US_help/symphonymat.html b/help/en_US/scilab_en_US_help/symphonymat.html
index 2e89728..611010b 100644
--- a/help/en_US/scilab_en_US_help/symphonymat.html
+++ b/help/en_US/scilab_en_US_help/symphonymat.html
@@ -12,7 +12,7 @@
     <div class="manualnavbar">
     <table width="100%"><tr>
       <td width="30%">
-    	<span class="previous"><a href="symphony_mat.html">&lt;&lt; symphony_mat</a></span>
+    	<span class="previous"><a href="symphony.html">&lt;&lt; symphony</a></span>
 
       </td>
       <td width="40%" class="center">
@@ -69,13 +69,13 @@
    <dt><span class="term">status :</span>
       <dd><p class="para">status flag from symphony.</p></dd></dt>
    <dt><span class="term">output :</span>
-      <dd><p class="para">The output data structure contains detailed informations about the optimization process.</p></dd></dt></dl></div>
+      <dd><p class="para">The output data structure contains detailed informations about the optimization process. Right now it contains number of iteration.</p></dd></dt></dl></div>
 
 <div class="refsection"><h3 class="title">Description</h3>
    <p class="para">Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
 find the minimum or maximum of f(x) such that</p>
-   <p class="para"><span><img src='./_LaTeX_symphonymat.xml_1.png' style='position:relative;top:40px;width:205px;height:88px'/></span></p>
-   <p class="para">We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.</p>
+   <p class="para"><span><img src='./_LaTeX_symphonymat.xml_1.png' style='position:relative;top:51px;width:216px;height:110px'/></span></p>
+   <p class="para">We are calling SYMPHONY written in C by gateway files for the actual computation.</p>
    <p class="para"></p></div>
 
 <div class="refsection"><h3 class="title">Examples</h3>
@@ -92,7 +92,8 @@ find the minimum or maximum of f(x) such that</p>
 <span class="scilabid">beq</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span> <span class="scilabnumber">25</span><span class="scilabdefault">,</span> <span class="scilabnumber">1.25</span><span class="scilabdefault">,</span> <span class="scilabnumber">1.25</span><span class="scilabopenclose">]</span>
 <span class="scilabid">intcon</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">1</span> <span class="scilabnumber">2</span> <span class="scilabnumber">3</span> <span class="scilabnumber">4</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
 <span class="scilabcomment">// Calling Symphony</span>
-<span class="scilabopenclose">[</span><span class="scilabid">x</span><span class="scilabdefault">,</span><span class="scilabid">f</span><span class="scilabdefault">,</span><span class="scilabid">status</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabopenclose">]</span> <span class="scilaboperator">=</span> <span class="scilabid">symphonymat</span><span class="scilabopenclose">(</span><span class="scilabid">c</span><span class="scilabdefault">,</span><span class="scilabid">intcon</span><span class="scilabdefault">,</span><span class="scilabopenclose">[</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabopenclose">[</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabid">Aeq</span><span class="scilabdefault">,</span><span class="scilabid">beq</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabopenclose">)</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
+<span class="scilabopenclose">[</span><span class="scilabid">x</span><span class="scilabdefault">,</span><span class="scilabid">f</span><span class="scilabdefault">,</span><span class="scilabid">status</span><span class="scilabdefault">,</span><span class="scilabid">output</span><span class="scilabopenclose">]</span> <span class="scilaboperator">=</span> <span class="scilabid">symphonymat</span><span class="scilabopenclose">(</span><span class="scilabid">c</span><span class="scilabdefault">,</span><span class="scilabid">intcon</span><span class="scilabdefault">,</span><span class="scilabopenclose">[</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabopenclose">[</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabid">Aeq</span><span class="scilabdefault">,</span><span class="scilabid">beq</span><span class="scilabdefault">,</span><span class="scilabid">lb</span><span class="scilabdefault">,</span><span class="scilabid">ub</span><span class="scilabopenclose">)</span>
+<span class="scilabcomment">// Press ENTER to continue</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
 
 <div class="refsection"><h3 class="title">Examples</h3>
    <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabcomment">// An advanced case where we set some options in symphony</span>
@@ -154,7 +155,7 @@ find the minimum or maximum of f(x) such that</p>
 <span class="scilabnumber">483</span> <span class="scilabnumber">336</span> <span class="scilabnumber">765</span> <span class="scilabnumber">637</span> <span class="scilabnumber">981</span> <span class="scilabnumber">980</span> <span class="scilabnumber">202</span> <span class="scilabnumber">35</span> <span class="scilabnumber">594</span> <span class="scilabnumber">689</span> <span class="scilabnumber">602</span> <span class="scilabnumber">76</span> <span class="scilabnumber">767</span> <span class="scilabnumber">693</span> <span class="scilabspecial">..</span>
 <span class="scilabnumber">893</span> <span class="scilabnumber">160</span> <span class="scilabnumber">785</span> <span class="scilabnumber">311</span> <span class="scilabnumber">417</span> <span class="scilabnumber">748</span> <span class="scilabnumber">375</span> <span class="scilabnumber">362</span> <span class="scilabnumber">617</span> <span class="scilabnumber">553</span> <span class="scilabnumber">474</span> <span class="scilabnumber">915</span> <span class="scilabnumber">457</span> <span class="scilabnumber">261</span> <span class="scilabnumber">350</span> <span class="scilabnumber">635</span> <span class="scilabdefault">;</span>
 <span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">nbVar</span> <span class="scilaboperator">=</span> <a class="scilabcommand" href="scilab://size">size</a><span class="scilabopenclose">(</span><span class="scilabid">objCoef</span><span class="scilabdefault">,</span><span class="scilabnumber">2</span><span class="scilabopenclose">)</span>
+<span class="scilabid">nbVar</span> <span class="scilaboperator">=</span> <a class="scilabcommand" href="scilab://size">size</a><span class="scilabopenclose">(</span><span class="scilabid">objCoef</span><span class="scilabdefault">,</span><span class="scilabnumber">1</span><span class="scilabopenclose">)</span>
 <span class="scilabid">conUB</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilabnumber">11927</span> <span class="scilabnumber">13727</span> <span class="scilabnumber">11551</span> <span class="scilabnumber">13056</span> <span class="scilabnumber">13460</span> <span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
 <span class="scilabcomment">// Lower Bound of variables</span>
 <span class="scilabid">lb</span> <span class="scilaboperator">=</span> <a class="scilabmacro" href="scilab://repmat">repmat</a><span class="scilabopenclose">(</span><span class="scilabnumber">0</span><span class="scilabdefault">,</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilabid">nbVar</span><span class="scilabopenclose">)</span>
@@ -185,7 +186,7 @@ find the minimum or maximum of f(x) such that</p>
     <tr><td colspan="3" class="next"><a href="http://bugzilla.scilab.org/enter_bug.cgi?product=Scilab%20software&component=Documentation%20pages" class="ulink">Report an issue</a></td></tr>
 <tr>
       <td width="30%">
-    	<span class="previous"><a href="symphony_mat.html">&lt;&lt; symphony_mat</a></span>
+    	<span class="previous"><a href="symphony.html">&lt;&lt; symphony</a></span>
 
       </td>
       <td width="40%" class="center">
diff --git a/help/en_US/symphony.xml b/help/en_US/symphony.xml
index a80f022..9fb615d 100644
--- a/help/en_US/symphony.xml
+++ b/help/en_US/symphony.xml
@@ -64,7 +64,7 @@
    <varlistentry><term>status :</term>
       <listitem><para> status flag from symphony.</para></listitem></varlistentry>
    <varlistentry><term>output :</term>
-      <listitem><para> The output data structure contains detailed informations about the optimization process.</para></listitem></varlistentry>
+      <listitem><para> The output data structure contains detailed informations about the optimization process. Right now it contains number of iteration.</para></listitem></varlistentry>
    </variablelist>
 </refsection>
 
@@ -78,14 +78,15 @@ find the minimum or maximum of f(x) such that
 <latex>
 \begin{eqnarray}
 &amp;\mbox{min}_{x}
-&amp; f(x) \\
-&amp; \text{subject to} &amp; conLB \leq C(x) \leq conUB \\
+&amp; f^T*x \\
+&amp; \text{subject to} &amp; conLB \leq C*x \leq conUB \\
 &amp; &amp; lb \leq x \leq ub \\
+&amp; &amp; x_i \in \!\, \mathbb{Z}, i \in \!\, I
 \end{eqnarray}
 </latex>
    </para>
    <para>
-We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.
+We are calling SYMPHONY written in C by gateway files for the actual computation.
    </para>
    <para>
 </para>
@@ -115,6 +116,7 @@ xopt = [1 1 0 1 7.25 0 0.25 3.5]
 fopt = [8495]
 // Calling Symphony
 [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1)
+// Press ENTER to continue
 
    ]]></programlisting>
 </refsection>
@@ -203,8 +205,7 @@ xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 ..
 // Optimal value
 fopt = [ 24381 ]
 // Calling Symphony
-[x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options)
-
+[x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options);
    ]]></programlisting>
 </refsection>
 
diff --git a/help/en_US/symphony_mat.xml b/help/en_US/symphony_mat.xml
deleted file mode 100644
index 4f6e9c9..0000000
--- a/help/en_US/symphony_mat.xml
+++ /dev/null
@@ -1,202 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-
-<!--
- *
- * This help file was generated from symphony_mat.sci using help_from_sci().
- *
- -->
-
-<refentry version="5.0-subset Scilab" xml:id="symphony_mat" xml:lang="en"
-          xmlns="http://docbook.org/ns/docbook"
-          xmlns:xlink="http://www.w3.org/1999/xlink"
-          xmlns:svg="http://www.w3.org/2000/svg"
-          xmlns:ns3="http://www.w3.org/1999/xhtml"
-          xmlns:mml="http://www.w3.org/1998/Math/MathML"
-          xmlns:scilab="http://www.scilab.org"
-          xmlns:db="http://docbook.org/ns/docbook">
-
-  <refnamediv>
-    <refname>symphony_mat</refname>
-    <refpurpose>Solves a mixed integer linear programming constrained optimization problem in intlinprog format.</refpurpose>
-  </refnamediv>
-
-
-<refsynopsisdiv>
-   <title>Calling Sequence</title>
-   <synopsis>
-   xopt = symphony_mat(f,intcon,A,b)
-   xopt = symphony_mat(f,intcon,A,b,Aeq,beq)
-   xopt = symphony_mat(f,intcon,A,b,Aeq,beq,lb,ub)
-   xopt = symphony_mat(f,intcon,A,b,Aeq,beq,lb,ub,options)
-   [xopt,fopt,status,output] = symphony_mat( ... )
-   
-   </synopsis>
-</refsynopsisdiv>
-
-<refsection>
-   <title>Parameters</title>
-   <variablelist>
-   <varlistentry><term>f :</term>
-      <listitem><para> a 1xn matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective</para></listitem></varlistentry>
-   <varlistentry><term>intcon :</term>
-      <listitem><para> Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable</para></listitem></varlistentry>
-   <varlistentry><term>A :</term>
-      <listitem><para> Linear inequality constraint matrix, specified as a matrix of doubles. A represents the linear coefficients in the constraints A*x ≤ b. A has size M-by-N, where M is the number of constraints and N is number of variables</para></listitem></varlistentry>
-   <varlistentry><term>b :</term>
-      <listitem><para> Linear inequality constraint vector, specified as a vector of doubles. b represents the constant vector in the constraints A*x ≤ b. b has length M, where A is M-by-N</para></listitem></varlistentry>
-   <varlistentry><term>Aeq :</term>
-      <listitem><para> Linear equality constraint matrix, specified as a matrix of doubles. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has size Meq-by-N, where Meq is the number of constraints and N is number of variables</para></listitem></varlistentry>
-   <varlistentry><term>beq :</term>
-      <listitem><para> Linear equality constraint vector, specified as a vector of doubles. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N.</para></listitem></varlistentry>
-   <varlistentry><term>lb :</term>
-      <listitem><para> Lower bounds, specified as a vector or array of doubles. lb represents the lower bounds elementwise in lb ≤ x ≤ ub.</para></listitem></varlistentry>
-   <varlistentry><term>ub :</term>
-      <listitem><para> Upper bounds, specified as a vector or array of doubles. ub represents the upper bounds elementwise in lb ≤ x ≤ ub.</para></listitem></varlistentry>
-   <varlistentry><term>options :</term>
-      <listitem><para> a 1xq marix of string, provided to set the paramters in symphony</para></listitem></varlistentry>
-   <varlistentry><term>xopt :</term>
-      <listitem><para> a 1xn matrix of doubles, the computed solution of the optimization problem</para></listitem></varlistentry>
-   <varlistentry><term>fopt :</term>
-      <listitem><para> a 1x1 matrix of doubles, the function value at x</para></listitem></varlistentry>
-   <varlistentry><term>output :</term>
-      <listitem><para> The output data structure contains detailed informations about the optimization process.</para></listitem></varlistentry>
-   </variablelist>
-</refsection>
-
-<refsection>
-   <title>Description</title>
-   <para>
-Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
-find the minimum or maximum of f(x) such that
-   </para>
-   <para>
-<latex>
-\begin{eqnarray}
-&amp;\mbox{min}_{x}
-&amp; f(x) \\
-&amp; \text{subject to} &amp; conLB \leq C(x) \leq conUB \\
-&amp; &amp; lb \leq x \leq ub \\
-\end{eqnarray}
-</latex>
-   </para>
-   <para>
-We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.
-   </para>
-   <para>
-</para>
-</refsection>
-
-<refsection>
-   <title>Examples</title>
-   <programlisting role="example"><![CDATA[
-// Objective function
-c = [350*5,330*3,310*4,280*6,500,450,400,100]
-// Lower Bound of variable
-lb = repmat(0,1,8);
-// Upper Bound of variables
-ub = [repmat(1,1,4) repmat(%inf,1,4)];
-// Constraint Matrix
-Aeq = [5,3,4,6,1,1,1,1;
-5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03;
-5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;]
-beq = [ 25, 1.25, 1.25]
-intcon = [1 2 3 4];
-// Calling Symphony
-[x,f,iter] = symphony_mat(c,intcon,[],[],Aeq,beq,lb,ub);
-
-   ]]></programlisting>
-</refsection>
-
-<refsection>
-   <title>Examples</title>
-   <programlisting role="example"><![CDATA[
-// An advanced case where we set some options in symphony
-// This problem is taken from
-// P.C.Chu and J.E.Beasley
-// "A genetic algorithm for the multidimensional knapsack problem",
-// Journal of Heuristics, vol. 4, 1998, pp63-86.
-// The problem to be solved is:
-// Max  sum{j=1,...,n} p(j)x(j)
-// st   sum{j=1,...,n} r(i,j)x(j) <= b(i)       i=1,...,m
-//                     x(j)=0 or 1
-// The function to be maximize i.e. P(j)
-objCoef = -1*[   504 803 667 1103 834 585 811 856 690 832 846 813 868 793 ..
-825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 ..
-877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 ..
-957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 ..
-959 668 507 855 986 831 821 825 868 852 832 828 799 686 ..
-510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 ..
-1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]
-//Constraint Matrix
-conMatrix = [   //Constraint 1
-42 41 523 215 819 551 69 193 582 375 367 478 162 898 ..
-550 553 298 577 493 183 260 224 852 394 958 282 402 604 ..
-164 308 218 61 273 772 191 117 276 877 415 873 902 465 ..
-320 870 244 781 86 622 665 155 680 101 665 227 597 354 ..
-597 79 162 998 849 136 112 751 735 884 71 449 266 420 ..
-797 945 746 46 44 545 882 72 383 714 987 183 731 301 ..
-718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298;
-//Constraint 2
-509 883 229 569 706 639 114 727 491 481 681 948 687 941 ..
-350 253 573 40 124 384 660 951 739 329 146 593 658 816 ..
-638 717 779 289 430 851 937 289 159 260 930 248 656 833 ..
-892 60 278 741 297 967 86 249 354 614 836 290 893 857 ..
-158 869 206 504 799 758 431 580 780 788 583 641 32 653 ..
-252 709 129 368 440 314 287 854 460 594 512 239 719 751 ..
-708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850;
-//Constraint 3
-806 361 199 781 596 669 957 358 259 888 319 751 275 177 ..
-883 749 229 265 282 694 819 77 190 551 140 442 867 283 ..
-137 359 445 58 440 192 485 744 844 969 50 833 57 877 ..
-482 732 968 113 486 710 439 747 174 260 877 474 841 422 ..
-280 684 330 910 791 322 404 403 519 148 948 414 894 147 ..
-73 297 97 651 380 67 582 973 143 732 624 518 847 113 ..
-382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ;
-//Constraint 4
-404 197 817 1000 44 307 39 659 46 334 448 599 931 776 ..
-263 980 807 378 278 841 700 210 542 636 388 129 203 110 ..
-817 502 657 804 662 989 585 645 113 436 610 948 919 115 ..
-967 13 445 449 740 592 327 167 368 335 179 909 825 614 ..
-987 350 179 415 821 525 774 283 427 275 659 392 73 896 ..
-68 982 697 421 246 672 649 731 191 514 983 886 95 846 ..
-689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322;
-//Constrain 5
-475 36 287 577 45 700 803 654 196 844 657 387 518 143 ..
-515 335 942 701 332 803 265 922 908 139 995 845 487 100 ..
-447 653 649 738 424 475 425 926 795 47 136 801 904 740 ..
-768 460 76 660 500 915 897 25 716 557 72 696 653 933 ..
-420 582 810 861 758 647 237 631 271 91 75 756 409 440 ..
-483 336 765 637 981 980 202 35 594 689 602 76 767 693 ..
-893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ;
-];
-nbVar = size(objCoef,2)
-conUB=[11927 13727 11551 13056 13460 ];
-// Lower Bound of variables
-lb = repmat(0,1,nbVar)
-// Upper Bound of variables
-ub = repmat(1,1,nbVar)
-// Lower Bound of constrains
-intcon = []
-for i = 1:nbVar
-intcon = [intcon i];
-end
-// The expected solution :
-// Output variables
-xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 ..
-0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 ..
-0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0]
-// Optimal value
-fopt = [ 24381 ]
-// Calling Symphony
-[x,f,iter] = symphony_mat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub);
-
-   ]]></programlisting>
-</refsection>
-
-<refsection>
-   <title>Authors</title>
-   <simplelist type="vert">
-   <member>Keyur Joshi, Saikiran, Iswarya, Harpreet Singh</member>
-   </simplelist>
-</refsection>
-</refentry>
diff --git a/help/en_US/symphonymat.xml b/help/en_US/symphonymat.xml
index d811582..ab2ca34 100644
--- a/help/en_US/symphonymat.xml
+++ b/help/en_US/symphonymat.xml
@@ -61,7 +61,7 @@
    <varlistentry><term>status :</term>
       <listitem><para> status flag from symphony.</para></listitem></varlistentry>
    <varlistentry><term>output :</term>
-      <listitem><para> The output data structure contains detailed informations about the optimization process.</para></listitem></varlistentry>
+      <listitem><para> The output data structure contains detailed informations about the optimization process. Right now it contains number of iteration.</para></listitem></varlistentry>
    </variablelist>
 </refsection>
 
@@ -75,15 +75,16 @@ find the minimum or maximum of f(x) such that
 <latex>
 \begin{eqnarray}
 &amp;\mbox{min}_{x}
-&amp; f(x) \\
-&amp; \text{subject to} &amp; A.x \leq b \\
-&amp; &amp; Aeq.x \leq beq \\
+&amp; f^T*x \\
+&amp; \text{subject to} &amp; A*x \leq b \\
+&amp; &amp; Aeq*x = beq \\
 &amp; &amp; lb \leq x \leq ub \\
+&amp; &amp; x_i \in \!\, \mathbb{Z}, i \in \!\, I
 \end{eqnarray}
 </latex>
    </para>
    <para>
-We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.
+We are calling SYMPHONY written in C by gateway files for the actual computation.
    </para>
    <para>
 </para>
@@ -106,6 +107,7 @@ beq = [ 25, 1.25, 1.25]
 intcon = [1 2 3 4];
 // Calling Symphony
 [x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub)
+// Press ENTER to continue
 
    ]]></programlisting>
 </refsection>
@@ -193,7 +195,6 @@ xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 ..
 fopt = [ 24381 ]
 // Calling Symphony
 [x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options);
-
    ]]></programlisting>
 </refsection>
 
diff --git a/jar/scilab_en_US_help.jar b/jar/scilab_en_US_help.jar
index 3357bbb..b17b700 100644
--- a/jar/scilab_en_US_help.jar
+++ b/jar/scilab_en_US_help.jar
diff --git a/macros/lsqlin.bin b/macros/lsqlin.bin
index 801025f..d7fccb3 100644
--- a/macros/lsqlin.bin
+++ b/macros/lsqlin.bin
diff --git a/macros/lsqlin.sci b/macros/lsqlin.sci
index 4a5fa2d..1dc1fd5 100644
--- a/macros/lsqlin.sci
+++ b/macros/lsqlin.sci
@@ -14,11 +14,11 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	// Solves a linear quadratic problem.
 	//
 	//   Calling Sequence
-	//   x = lsqlin(C,d,A,b)
-	//   x = lsqlin(C,d,A,b,Aeq,beq)
-	//   x = lsqlin(C,d,A,b,Aeq,beq,lb,ub)
-	//   x = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0)
-	//   x = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0,param)
+	//   xopt = lsqlin(C,d,A,b)
+	//   xopt = lsqlin(C,d,A,b,Aeq,beq)
+	//   xopt = lsqlin(C,d,A,b,Aeq,beq,lb,ub)
+	//   xopt = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0)
+	//   xopt = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0,param)
 	//   [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin( ... )
 	//   
 	//   Parameters
@@ -36,8 +36,8 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	//   resnorm : a double, objective value returned as the scalar value norm(C*x-d)^2.
 	//   residual : a vector of doubles, solution residuals returned as the vector C*x-d.
 	//   exitflag : Integer identifying the reason the algorithm terminated.
-	//   output : Structure containing information about the optimization.
-	//   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).
+	//   output : Structure containing information about the optimization. Right now it contains number of iteration.
+	//   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.
 	//   
 	//   Description
 	//   Search the minimum of a constrained linear least square problem specified by :
@@ -46,13 +46,13 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	//    \begin{eqnarray}
 	//    &\mbox{min}_{x}
 	//    & 1/2||C*x - d||_2^2  \\
-	//    & \text{subject to} & A.x \leq b \\
-	//    & & Aeq.x \leq beq \\
+	//    & \text{subject to} & A*x \leq b \\
+	//    & & Aeq*x = beq \\
 	//    & & lb \leq x \leq ub \\
 	//    \end{eqnarray}
 	//   </latex>
 	//   
-	//   We are calling IPOpt for solving the linear least square problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.
+	//   We are calling IPOpt for solving the linear least square problem, IPOpt is a library written in C++.
 	//
 	// Examples
 	// //A simple linear least square example
@@ -73,8 +73,10 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	//     0.2026
 	//     0.6721];
 	// [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin(C,d,A,b)
+	// // Press ENTER to continue 
 	//    
-	// Examples 
+	// Examples
+	// //A basic example for equality, inequality and bounds
 	// C = [0.9501    0.7620    0.6153    0.4057
 	//     0.2311    0.4564    0.7919    0.9354
 	//     0.6068    0.0185    0.9218    0.9169
@@ -96,7 +98,6 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	// lb = -0.1*ones(4,1);
 	// ub = 2*ones(4,1);
 	// [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin(C,d,A,b,Aeq,beq,lb,ub)
-	//
 	// Authors
 	// Harpreet Singh
 
diff --git a/macros/lsqnonneg.bin b/macros/lsqnonneg.bin
index cd8a04a..84e307b 100644
--- a/macros/lsqnonneg.bin
+++ b/macros/lsqnonneg.bin
diff --git a/macros/lsqnonneg.sci b/macros/lsqnonneg.sci
index 77e5e44..b8694b4 100644
--- a/macros/lsqnonneg.sci
+++ b/macros/lsqnonneg.sci
@@ -14,8 +14,8 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 	// Solves nonnegative least-squares curve fitting problems.
 	//
 	//   Calling Sequence
-	//   x = lsqnonneg(C,d)
-	//   x = lsqnonneg(C,d,param)
+	//   xopt = lsqnonneg(C,d)
+	//   xopt = lsqnonneg(C,d,param)
 	//   [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg( ... )
 	//   
 	//   Parameters
@@ -25,8 +25,8 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 	//   resnorm : a double, objective value returned as the scalar value norm(C*x-d)^2.
 	//   residual : a vector of doubles, solution residuals returned as the vector C*x-d.
 	//   exitflag : Integer identifying the reason the algorithm terminated.
-	//   output : Structure containing information about the optimization.
-	//   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).
+	//   output : Structure containing information about the optimization. Right now it contains number of iteration.
+	//   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.
 	//   
 	//   Description
 	//   Solves nonnegative least-squares curve fitting problems specified by :
@@ -39,10 +39,10 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 	//    \end{eqnarray}
 	//   </latex>
 	//   
-	//   We are calling IPOpt for solving the nonnegative least-squares curve fitting problems, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.
+	//   We are calling IPOpt for solving the nonnegative least-squares curve fitting problems, IPOpt is a library written in C++.
 	//    
 	// Examples 
-	// A basic lsqnonneg problem
+	// // A basic lsqnonneg problem
 	//	C = [
 	//		0.0372    0.2869
 	//		0.6861    0.7071
@@ -54,7 +54,6 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 	//   	0.0747
 	//	    0.8405];
 	// [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg(C,d)
-	//
 	// Authors
 	// Harpreet Singh
 
diff --git a/macros/qpipopt.bin b/macros/qpipopt.bin
index 2fd432e..584f327 100644
--- a/macros/qpipopt.bin
+++ b/macros/qpipopt.bin
diff --git a/macros/qpipopt.sci b/macros/qpipopt.sci
index 8b7cecd..affd061 100644
--- a/macros/qpipopt.sci
+++ b/macros/qpipopt.sci
@@ -34,8 +34,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //   xopt : a vector of doubles, the computed solution of the optimization problem.
   //   fopt : a double, the function value at x.
   //   exitflag : Integer identifying the reason the algorithm terminated.
-  //   output : Structure containing information about the optimization.
-  //   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).
+  //   output : Structure containing information about the optimization. Right now it contains number of iteration.
+  //   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.
   //   
   //   Description
   //   Search the minimum of a constrained linear quadratic optimization problem specified by :
@@ -50,7 +50,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //    \end{eqnarray}
   //   </latex>
   //   
-  //   We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.
+  //   We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++.
   //
   // Examples
   //      //Find x in R^6 such that:
@@ -70,6 +70,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //      x0 = repmat(0,nbVar,1);
   //	  param = list("MaxIter", 300, "CpuTime", 100);
   //      [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param)
+  // // Press ENTER to continue
   //    
   // Examples 
   //    //Find the value of x that minimize following function
@@ -89,7 +90,6 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //	nbVar = 2;
   //	nbCon = 3;
   //	[xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
-  // 
   // Authors
   // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
     
diff --git a/macros/qpipoptmat.bin b/macros/qpipoptmat.bin
index 7a37d9a..ad893f2 100644
--- a/macros/qpipoptmat.bin
+++ b/macros/qpipoptmat.bin
diff --git a/macros/qpipoptmat.sci b/macros/qpipoptmat.sci
index 3f58e70..eec93ce 100644
--- a/macros/qpipoptmat.sci
+++ b/macros/qpipoptmat.sci
@@ -11,87 +11,85 @@
 
 
 function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
-  // Solves a linear quadratic problem.
-  //
-  //   Calling Sequence
-  //   x = qpipoptmat(H,f)
-  //   x = qpipoptmat(H,f,A,b)
-  //   x = qpipoptmat(H,f,A,b,Aeq,beq)
-  //   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub)
-  //   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0)
-  //   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param)
-  //   [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... )
-  //   
-  //   Parameters
-  //   H : a symmetric matrix of doubles, represents coefficients of quadratic in the quadratic problem.
-  //   f : a vector of doubles, represents coefficients of linear in the quadratic problem
-  //   A : a vector of doubles, represents the linear coefficients in the inequality constraints
-  //   b : a vector of doubles, represents the linear coefficients in the inequality constraints
-  //   Aeq : a matrix of doubles, represents the linear coefficients in the equality constraints
-  //   beq : a vector of doubles, represents the linear coefficients in the equality constraints
-  //   LB : a vector of doubles, contains lower bounds of the variables.
-  //   UB : a vector of doubles, contains upper bounds of the variables.
-  //   x0 : a vector of doubles, contains initial guess of variables.
-  //   param : a list containing the the parameters to be set.
-  //   xopt : a vector of doubles, the computed solution of the optimization problem.
-  //   fopt : a double, the function value at x.
-  //   exitflag : Integer identifying the reason the algorithm terminated.
-  //   output : Structure containing information about the optimization.
-  //   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).
-  //   
-  //   Description
-  //   Search the minimum of a constrained linear quadratic optimization problem specified by :
-  //   find the minimum of f(x) such that 
-  //
-  //   <latex>
-  //    \begin{eqnarray}
-  //    &\mbox{min}_{x}
-  //    & 1/2*x'*H*x + f'*x  \\
-  //    & \text{subject to} & A.x \leq b \\
-  //    & & Aeq.x \leq beq \\
-  //    & & lb \leq x \leq ub \\
-  //    \end{eqnarray}
-  //   </latex>
-  //   
-  //   We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.
-  //
-  // Examples
-  //      //Find x in R^6 such that:
-  //      
-  //      Aeq= [1,-1,1,0,3,1;
-  //           -1,0,-3,-4,5,6;
-  //           2,5,3,0,1,0];
-  //      beq=[1; 2; 3];
-  //      A= [0,1,0,1,2,-1;
-  //          -1,0,2,1,1,0];
-  //      b = [-1; 2.5];
-  //      lb=[-1000; -10000; 0; -1000; -1000; -1000];
-  //      ub=[10000; 100; 1.5; 100; 100; 1000];
-  //      x0 = repmat(0,6,1);
-  //	  param = list("MaxIter", 300, "CpuTime", 100);
-  //      //and minimize 0.5*x'*Q*x + p'*x with
-  //      f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
-  //      [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param)
-  //      clear H f A b Aeq beq lb ub;
-  //    
-  // Examples 
-  //    //Find the value of x that minimize following function
-  //    // f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2
-  //    // Subject to:
-  //    // x1 + x2 ≤ 2
-  //    // –x1 + 2x2 ≤ 2
-  //    // 2x1 + x2 ≤ 3
-  //    // 0 ≤ x1, 0 ≤ x2.
-  //	H = [1 -1; -1 2]; 
-  //	f = [-2; -6];
-  //    A = [1 1; -1 2; 2 1];
-  //	b = [2; 2; 3];
-  //	lb = [0; 0];
-  //	ub = [%inf; %inf];
-  //	[xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub)
-  //
-  // Authors
-  // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
+	// Solves a linear quadratic problem.
+	//
+	//   Calling Sequence
+	//   xopt = qpipoptmat(H,f)
+	//   xopt = qpipoptmat(H,f,A,b)
+	//   xopt = qpipoptmat(H,f,A,b,Aeq,beq)
+	//   xopt = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub)
+	//   xopt = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0)
+	//   xopt = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param)
+	//   [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... )
+	//   
+	//   Parameters
+	//   H : a symmetric matrix of doubles, represents coefficients of quadratic in the quadratic problem.
+	//   f : a vector of doubles, represents coefficients of linear in the quadratic problem
+	//   A : a vector of doubles, represents the linear coefficients in the inequality constraints
+	//   b : a vector of doubles, represents the linear coefficients in the inequality constraints
+	//   Aeq : a matrix of doubles, represents the linear coefficients in the equality constraints
+	//   beq : a vector of doubles, represents the linear coefficients in the equality constraints
+	//   LB : a vector of doubles, contains lower bounds of the variables.
+	//   UB : a vector of doubles, contains upper bounds of the variables.
+	//   x0 : a vector of doubles, contains initial guess of variables.
+	//   param : a list containing the the parameters to be set.
+	//   xopt : a vector of doubles, the computed solution of the optimization problem.
+	//   fopt : a double, the function value at x.
+	//   exitflag : Integer identifying the reason the algorithm terminated.
+	//   output : Structure containing information about the optimization. Right now it contains number of iteration.
+	//   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.
+	//   
+	//   Description
+	//   Search the minimum of a constrained linear quadratic optimization problem specified by :
+	//   find the minimum of f(x) such that 
+	//
+	//   <latex>
+	//    \begin{eqnarray}
+	//    &\mbox{min}_{x}
+	//    & 1/2*x'*H*x + f'*x  \\
+	//    & \text{subject to} & A*x \leq b \\
+	//    & & Aeq*x = beq \\
+	//    & & lb \leq x \leq ub \\
+	//    \end{eqnarray}
+	//   </latex>
+	//   
+	//   We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++.
+	//
+	// Examples
+	//    //Find the value of x that minimize following function
+	//    // f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2
+	//    // Subject to:
+	//    // x1 + x2 ≤ 2
+	//    // –x1 + 2x2 ≤ 2
+	//    // 2x1 + x2 ≤ 3
+	//    // 0 ≤ x1, 0 ≤ x2.
+	//	H = [1 -1; -1 2]; 
+	//	f = [-2; -6];
+	//    A = [1 1; -1 2; 2 1];
+	//	b = [2; 2; 3];
+	//	lb = [0; 0];
+	//	ub = [%inf; %inf];
+	//	[xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub)
+	// // Press ENTER to continue 
+	//
+	// Examples 
+	//      //Find x in R^6 such that:
+	//      Aeq= [1,-1,1,0,3,1;
+	//           -1,0,-3,-4,5,6;
+	//           2,5,3,0,1,0];
+	//      beq=[1; 2; 3];
+	//      A= [0,1,0,1,2,-1;
+	//          -1,0,2,1,1,0];
+	//      b = [-1; 2.5];
+	//      lb=[-1000; -10000; 0; -1000; -1000; -1000];
+	//      ub=[10000; 100; 1.5; 100; 100; 1000];
+	//      x0 = repmat(0,6,1);
+	//	  param = list("MaxIter", 300, "CpuTime", 100);
+	//      //and minimize 0.5*x'*Q*x + p'*x with
+	//      f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
+	//      [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param)
+	// Authors
+	// Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
     
     
 //To check the number of input and output argument
diff --git a/macros/symphony.bin b/macros/symphony.bin
index 3dab926..4bca695 100644
--- a/macros/symphony.bin
+++ b/macros/symphony.bin
diff --git a/macros/symphony.sci b/macros/symphony.sci
index eba9e64..b1a6f28 100644
--- a/macros/symphony.sci
+++ b/macros/symphony.sci
@@ -10,155 +10,156 @@
 // http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
 
 function [xopt,fopt,status,output] = symphony (varargin)
-  // Solves a  mixed integer linear programming constrained optimization problem.
-  //
-  //   Calling Sequence
-  //   xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB)
-  //   xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense)
-  //   xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options)
-  //   [xopt,fopt,status,output] = symphony( ... )
-  //   
-  //   Parameters
-  //   nbVar : a double, number of variables.
-  //   nbCon : a double, number of constraints.
-  //   objCoeff : a vector of doubles, represents coefficients of the variables in the objective.
-  //   isInt : a vector of boolean, represents wether a variable is constrained to be an integer.
-  //   LB : a vector of doubles, represents lower bounds of the variables.
-  //   UB : a vector of doubles, represents upper bounds of the variables.
-  //   conMatrix : a matrix of doubles, represents  matrix representing the constraint matrix.
-  //   conLB : a vector of doubles, represents lower bounds of the constraints. 
-  //   conUB : a vector of doubles, represents upper bounds of the constraints
-  //   objSense : The sense (maximization/minimization) of the objective. Use 1(sym_minimize ) or -1 (sym_maximize) here.
-  //   options : a a list containing the the parameters to be set.
-  //   xopt : a vector of doubles, the computed solution of the optimization problem.
-  //   fopt : a double, the function value at x.
-  //   status : status flag from symphony.
-  //   output : The output data structure contains detailed informations about the optimization process.
-  //   
-  //   Description
-  //   Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
-  //   find the minimum or maximum of f(x) such that 
-  //
-  //   <latex>
-  //    \begin{eqnarray}
-  //    &\mbox{min}_{x}
-  //    & f(x) \\
-  //    & \text{subject to} & conLB \leq C(x) \leq conUB \\
-  //    & & lb \leq x \leq ub \\
-  //    \end{eqnarray}
-  //   </latex>
-  //   
-  //   We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.
-  //
-  //   Examples
-  //    //A basic case : 
-  //    // Objective function
-  //    c = [350*5,330*3,310*4,280*6,500,450,400,100]';
-  //    // Lower Bound of variable
-  //    lb = repmat(0,8,1);
-  //    // Upper Bound of variables
-  //    ub = [repmat(1,4,1);repmat(%inf,4,1)];
-  //    // Constraint Matrix
-  //    conMatrix = [5,3,4,6,1,1,1,1;
-  //                 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03;
-  //                 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;]
-  //    // Lower Bound of constrains
-  //    conlb = [ 25; 1.25; 1.25]
-  //    // Upper Bound of constrains
-  //    conub = [ 25; 1.25; 1.25]
-  //    // Row Matrix for telling symphony that the is integer or not
-  //    isInt = [repmat(%t,1,4) repmat(%f,1,4)];
-  //    xopt = [1 1 0 1 7.25 0 0.25 3.5]
-  //    fopt = [8495]
-  //    // Calling Symphony
-  //    [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1)
-  //
-    //    Examples
-    //    // An advanced case where we set some options in symphony
-    //    // This problem is taken from 
-    //    // P.C.Chu and J.E.Beasley 
-    //    // "A genetic algorithm for the multidimensional knapsack problem",
-    //    // Journal of Heuristics, vol. 4, 1998, pp63-86.
-    //    // The problem to be solved is:
-    //    // Max  sum{j=1,...,n} p(j)x(j)
-    //    // st   sum{j=1,...,n} r(i,j)x(j) <= b(i)       i=1,...,m
-    //    //                     x(j)=0 or 1
-    //    // The function to be maximize i.e. P(j)
-    //    p = [   504 803 667 1103 834 585 811 856 690 832 846 813 868 793 ..
-    //            825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 ..
-    //            877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 ..
-    //            957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 ..
-    //            959 668 507 855 986 831 821 825 868 852 832 828 799 686 ..
-    //            510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 ..
-    //            1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]';
-    //    //Constraint Matrix
-    //    conMatrix = [ 
-    //                    //Constraint 1
-    //                    42 41 523 215 819 551 69 193 582 375 367 478 162 898 ..
-    //                    550 553 298 577 493 183 260 224 852 394 958 282 402 604 ..
-    //                    164 308 218 61 273 772 191 117 276 877 415 873 902 465 ..
-    //                    320 870 244 781 86 622 665 155 680 101 665 227 597 354 ..
-    //                    597 79 162 998 849 136 112 751 735 884 71 449 266 420 ..
-    //                    797 945 746 46 44 545 882 72 383 714 987 183 731 301 ..
-    //                    718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298;
-    //                    //Constraint 2
-    //                    509 883 229 569 706 639 114 727 491 481 681 948 687 941 ..
-    //                    350 253 573 40 124 384 660 951 739 329 146 593 658 816 ..
-    //                    638 717 779 289 430 851 937 289 159 260 930 248 656 833 ..
-    //                    892 60 278 741 297 967 86 249 354 614 836 290 893 857 ..
-    //                    158 869 206 504 799 758 431 580 780 788 583 641 32 653 ..
-    //                    252 709 129 368 440 314 287 854 460 594 512 239 719 751 ..
-    //                    708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850;
-    //                    //Constraint 3
-    //                    806 361 199 781 596 669 957 358 259 888 319 751 275 177 ..
-    //                    883 749 229 265 282 694 819 77 190 551 140 442 867 283 ..
-    //                    137 359 445 58 440 192 485 744 844 969 50 833 57 877 ..
-    //                    482 732 968 113 486 710 439 747 174 260 877 474 841 422 ..
-    //                    280 684 330 910 791 322 404 403 519 148 948 414 894 147 ..
-    //                    73 297 97 651 380 67 582 973 143 732 624 518 847 113 ..
-    //                    382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ;
-    //                    //Constraint 4
-    //                    404 197 817 1000 44 307 39 659 46 334 448 599 931 776 ..
-    //                    263 980 807 378 278 841 700 210 542 636 388 129 203 110 ..
-    //                    817 502 657 804 662 989 585 645 113 436 610 948 919 115 ..
-    //                    967 13 445 449 740 592 327 167 368 335 179 909 825 614 ..
-    //                    987 350 179 415 821 525 774 283 427 275 659 392 73 896 ..
-    //                    68 982 697 421 246 672 649 731 191 514 983 886 95 846 ..
-    //                    689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322;
-    //                    //Constrain 5
-    //                    475 36 287 577 45 700 803 654 196 844 657 387 518 143 ..
-    //                    515 335 942 701 332 803 265 922 908 139 995 845 487 100 ..
-    //                    447 653 649 738 424 475 425 926 795 47 136 801 904 740 ..
-    //                    768 460 76 660 500 915 897 25 716 557 72 696 653 933 ..
-    //                    420 582 810 861 758 647 237 631 271 91 75 756 409 440 ..
-    //                    483 336 765 637 981 980 202 35 594 689 602 76 767 693 ..
-    //                    893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ;
-    //     ];
-    //    nbCon = size(conMatrix,1)
-    //    nbVar = size(conMatrix,2)
-    //    // Lower Bound of variables
-    //    lb = repmat(0,nbVar,1)
-    //    // Upper Bound of variables
-    //    ub = repmat(1,nbVar,1)
-    //    // Row Matrix for telling symphony that the is integer or not
-    //    isInt = repmat(%t,1,nbVar)
-    //    // Lower Bound of constrains
-    //    conLB=repmat(0,nbCon,1);
-    //    // Upper Bound of constraints
-    //    conUB=[11927 13727 11551 13056 13460 ]';
-    //    options = list("time_limit", 25);
-    //    // The expected solution :
-    //    // Output variables
-    //    xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. 
-    //            0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 1 0 ..
-    //            0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0]
-    //    // Optimal value
-    //    fopt = [ 24381 ]
-    //    // Calling Symphony
-    //    [x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options)
-    //
-    // Authors
-    // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
+	// Solves a  mixed integer linear programming constrained optimization problem.
+	//
+	//   Calling Sequence
+	//   xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB)
+	//   xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense)
+	//   xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options)
+	//   [xopt,fopt,status,output] = symphony( ... )
+	//   
+	//   Parameters
+	//   nbVar : a double, number of variables.
+	//   nbCon : a double, number of constraints.
+	//   objCoeff : a vector of doubles, represents coefficients of the variables in the objective.
+	//   isInt : a vector of boolean, represents wether a variable is constrained to be an integer.
+	//   LB : a vector of doubles, represents lower bounds of the variables.
+	//   UB : a vector of doubles, represents upper bounds of the variables.
+	//   conMatrix : a matrix of doubles, represents  matrix representing the constraint matrix.
+	//   conLB : a vector of doubles, represents lower bounds of the constraints. 
+	//   conUB : a vector of doubles, represents upper bounds of the constraints
+	//   objSense : The sense (maximization/minimization) of the objective. Use 1(sym_minimize ) or -1 (sym_maximize) here.
+	//   options : a a list containing the the parameters to be set.
+	//   xopt : a vector of doubles, the computed solution of the optimization problem.
+	//   fopt : a double, the function value at x.
+	//   status : status flag from symphony.
+	//   output : The output data structure contains detailed informations about the optimization process. Right now it contains number of iteration.
+	//   
+	//   Description
+	//   Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
+	//   find the minimum or maximum of f(x) such that 
+	//
+	//   <latex>
+	//    \begin{eqnarray}
+	//    &\mbox{min}_{x}
+	//    & f^T*x \\
+	//    & \text{subject to} & conLB \leq C*x \leq conUB \\
+	//    & & lb \leq x \leq ub \\
+	//    & & x_i \in \!\, \mathbb{Z}, i \in \!\, I
+	//    \end{eqnarray}
+	//   </latex>
+	//   
+	//   We are calling SYMPHONY written in C by gateway files for the actual computation.
+	//
+	//   Examples
+	//    //A basic case : 
+	//    // Objective function
+	//    c = [350*5,330*3,310*4,280*6,500,450,400,100]';
+	//    // Lower Bound of variable
+	//    lb = repmat(0,8,1);
+	//    // Upper Bound of variables
+	//    ub = [repmat(1,4,1);repmat(%inf,4,1)];
+	//    // Constraint Matrix
+	//    conMatrix = [5,3,4,6,1,1,1,1;
+	//                 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03;
+	//                 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;]
+	//    // Lower Bound of constrains
+	//    conlb = [ 25; 1.25; 1.25]
+	//    // Upper Bound of constrains
+	//    conub = [ 25; 1.25; 1.25]
+	//    // Row Matrix for telling symphony that the is integer or not
+	//    isInt = [repmat(%t,1,4) repmat(%f,1,4)];
+	//    xopt = [1 1 0 1 7.25 0 0.25 3.5]
+	//    fopt = [8495]
+	//    // Calling Symphony
+	//    [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1)
+	//    // Press ENTER to continue 
+	//
+	//    Examples
+	//    // An advanced case where we set some options in symphony
+	//    // This problem is taken from 
+	//    // P.C.Chu and J.E.Beasley 
+	//    // "A genetic algorithm for the multidimensional knapsack problem",
+	//    // Journal of Heuristics, vol. 4, 1998, pp63-86.
+	//    // The problem to be solved is:
+	//    // Max  sum{j=1,...,n} p(j)x(j)
+	//    // st   sum{j=1,...,n} r(i,j)x(j) <= b(i)       i=1,...,m
+	//    //                     x(j)=0 or 1
+	//    // The function to be maximize i.e. P(j)
+	//    p = [   504 803 667 1103 834 585 811 856 690 832 846 813 868 793 ..
+	//            825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 ..
+	//            877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 ..
+	//            957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 ..
+	//            959 668 507 855 986 831 821 825 868 852 832 828 799 686 ..
+	//            510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 ..
+	//            1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]';
+	//    //Constraint Matrix
+	//    conMatrix = [ 
+	//                    //Constraint 1
+	//                    42 41 523 215 819 551 69 193 582 375 367 478 162 898 ..
+	//                    550 553 298 577 493 183 260 224 852 394 958 282 402 604 ..
+	//                    164 308 218 61 273 772 191 117 276 877 415 873 902 465 ..
+	//                    320 870 244 781 86 622 665 155 680 101 665 227 597 354 ..
+	//                    597 79 162 998 849 136 112 751 735 884 71 449 266 420 ..
+	//                    797 945 746 46 44 545 882 72 383 714 987 183 731 301 ..
+	//                    718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298;
+	//                    //Constraint 2
+	//                    509 883 229 569 706 639 114 727 491 481 681 948 687 941 ..
+	//                    350 253 573 40 124 384 660 951 739 329 146 593 658 816 ..
+	//                    638 717 779 289 430 851 937 289 159 260 930 248 656 833 ..
+	//                    892 60 278 741 297 967 86 249 354 614 836 290 893 857 ..
+	//                    158 869 206 504 799 758 431 580 780 788 583 641 32 653 ..
+	//                    252 709 129 368 440 314 287 854 460 594 512 239 719 751 ..
+	//                    708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850;
+	//                    //Constraint 3
+	//                    806 361 199 781 596 669 957 358 259 888 319 751 275 177 ..
+	//                    883 749 229 265 282 694 819 77 190 551 140 442 867 283 ..
+	//                    137 359 445 58 440 192 485 744 844 969 50 833 57 877 ..
+	//                    482 732 968 113 486 710 439 747 174 260 877 474 841 422 ..
+	//                    280 684 330 910 791 322 404 403 519 148 948 414 894 147 ..
+	//                    73 297 97 651 380 67 582 973 143 732 624 518 847 113 ..
+	//                    382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ;
+	//                    //Constraint 4
+	//                    404 197 817 1000 44 307 39 659 46 334 448 599 931 776 ..
+	//                    263 980 807 378 278 841 700 210 542 636 388 129 203 110 ..
+	//                    817 502 657 804 662 989 585 645 113 436 610 948 919 115 ..
+	//                    967 13 445 449 740 592 327 167 368 335 179 909 825 614 ..
+	//                    987 350 179 415 821 525 774 283 427 275 659 392 73 896 ..
+	//                    68 982 697 421 246 672 649 731 191 514 983 886 95 846 ..
+	//                    689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322;
+	//                    //Constrain 5
+	//                    475 36 287 577 45 700 803 654 196 844 657 387 518 143 ..
+	//                    515 335 942 701 332 803 265 922 908 139 995 845 487 100 ..
+	//                    447 653 649 738 424 475 425 926 795 47 136 801 904 740 ..
+	//                    768 460 76 660 500 915 897 25 716 557 72 696 653 933 ..
+	//                    420 582 810 861 758 647 237 631 271 91 75 756 409 440 ..
+	//                    483 336 765 637 981 980 202 35 594 689 602 76 767 693 ..
+	//                    893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ;
+	//     ];
+	//    nbCon = size(conMatrix,1)
+	//    nbVar = size(conMatrix,2)
+	//    // Lower Bound of variables
+	//    lb = repmat(0,nbVar,1)
+	//    // Upper Bound of variables
+	//    ub = repmat(1,nbVar,1)
+	//    // Row Matrix for telling symphony that the is integer or not
+	//    isInt = repmat(%t,1,nbVar)
+	//    // Lower Bound of constrains
+	//    conLB=repmat(0,nbCon,1);
+	//    // Upper Bound of constraints
+	//    conUB=[11927 13727 11551 13056 13460 ]';
+	//    options = list("time_limit", 25);
+	//    // The expected solution :
+	//    // Output variables
+	//    xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. 
+	//            0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 1 0 ..
+	//            0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0]
+	//    // Optimal value
+	//    fopt = [ 24381 ]
+	//    // Calling Symphony
+	//    [x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options);
+	// Authors
+	// Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
     
 //To check the number of input and output argument
    [lhs , rhs] = argn();
diff --git a/macros/symphonymat.bin b/macros/symphonymat.bin
index 8d42926..08b1616 100644
--- a/macros/symphonymat.bin
+++ b/macros/symphonymat.bin
diff --git a/macros/symphonymat.sci b/macros/symphonymat.sci
index 5aab6e5..40b07eb 100644
--- a/macros/symphonymat.sci
+++ b/macros/symphonymat.sci
@@ -32,7 +32,7 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
   //   xopt : a vector of double, the computed solution of the optimization problem
   //   fopt : a doubles, the function value at x
   //   status : status flag from symphony.
-  //   output : The output data structure contains detailed informations about the optimization process.
+  //   output : The output data structure contains detailed informations about the optimization process. Right now it contains number of iteration.
   //   
   //   Description
   //   Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
@@ -41,14 +41,15 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
   //   <latex>
   //    \begin{eqnarray}
   //    &\mbox{min}_{x}
-  //    & f(x) \\
-  //    & \text{subject to} & A.x \leq b \\
-  //    & & Aeq.x \leq beq \\
+  //    & f^T*x \\
+  //    & \text{subject to} & A*x \leq b \\
+  //    & & Aeq*x = beq \\
   //    & & lb \leq x \leq ub \\
+  //	& & x_i \in \!\, \mathbb{Z}, i \in \!\, I
   //    \end{eqnarray}
   //   </latex>
   //   
-  //   We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.
+  //   We are calling SYMPHONY written in C by gateway files for the actual computation.
   //
   // Examples
   //    // Objective function
@@ -65,6 +66,7 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
   //    intcon = [1 2 3 4];
   //    // Calling Symphony
   //    [x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub)
+  //	// Press ENTER to continue 
   //
   // Examples 
   //    // An advanced case where we set some options in symphony
@@ -147,7 +149,6 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
   //    fopt = [ 24381 ]
   //    // Calling Symphony
   //    [x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options);
-  // 
   // Authors
   // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
     
diff --git a/sci_gateway/cpp/libFAMOS.so b/sci_gateway/cpp/libFAMOS.so
index d4464aa..ccad147 100755
--- a/sci_gateway/cpp/libFAMOS.so
+++ b/sci_gateway/cpp/libFAMOS.so
diff --git a/tests/unit_tests/lsqlin.dia.ref b/tests/unit_tests/lsqlin.dia.ref
index a2b9630..9fbe23f 100644
--- a/tests/unit_tests/lsqlin.dia.ref
+++ b/tests/unit_tests/lsqlin.dia.ref
@@ -76,7 +76,7 @@ C = [0.9501    0.7620    0.6153    0.4057
  [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin(C,d,A,b,Aeq,beq,lb,ub)
 
 assert_close ( xopt , [ -0.1, -0.1, 0.1599089, 0.4089598 ]' , 0.0005 );
-assert_close ( residual , [ 0.0352969 0.0876228 -0.3532508 0.1452700 0.1212324 ]' , 0.0005 );
+assert_close ( residual , [-0.0352969 -0.0876228 0.3532508 -0.1452700 -0.1212324  ]' , 0.0005 );
 assert_close ( resnorm , [ 0.1695104] , 0.0005 );
-
 assert_checkequal( exitflag , int32(0) );
+printf("Test Successful");
diff --git a/tests/unit_tests/lsqlin.tst b/tests/unit_tests/lsqlin.tst
index a2b9630..9fbe23f 100644
--- a/tests/unit_tests/lsqlin.tst
+++ b/tests/unit_tests/lsqlin.tst
@@ -76,7 +76,7 @@ C = [0.9501    0.7620    0.6153    0.4057
  [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin(C,d,A,b,Aeq,beq,lb,ub)
 
 assert_close ( xopt , [ -0.1, -0.1, 0.1599089, 0.4089598 ]' , 0.0005 );
-assert_close ( residual , [ 0.0352969 0.0876228 -0.3532508 0.1452700 0.1212324 ]' , 0.0005 );
+assert_close ( residual , [-0.0352969 -0.0876228 0.3532508 -0.1452700 -0.1212324  ]' , 0.0005 );
 assert_close ( resnorm , [ 0.1695104] , 0.0005 );
-
 assert_checkequal( exitflag , int32(0) );
+printf("Test Successful");
diff --git a/tests/unit_tests/qpipopt_base.dia.ref b/tests/unit_tests/qpipopt_base.dia.ref
index 5587ddc..0cc59f1 100644
--- a/tests/unit_tests/qpipopt_base.dia.ref
+++ b/tests/unit_tests/qpipopt_base.dia.ref
@@ -72,5 +72,5 @@ nbCon = 3;
 
 assert_close ( xopt , [0.6666667 1.3333333]' , 1.e-7 );
 assert_close ( fopt , [ - 8.2222223] , 1.e-7 );
-
 assert_checkequal( exitflag , int32(0) );
+printf("Test Successful");
diff --git a/tests/unit_tests/qpipopt_base.tst b/tests/unit_tests/qpipopt_base.tst
index 5587ddc..eee8b91 100644
--- a/tests/unit_tests/qpipopt_base.tst
+++ b/tests/unit_tests/qpipopt_base.tst
@@ -74,3 +74,4 @@ assert_close ( xopt , [0.6666667 1.3333333]' , 1.e-7 );
 assert_close ( fopt , [ - 8.2222223] , 1.e-7 );
 
 assert_checkequal( exitflag , int32(0) );
+printf("Test Successfull")
diff --git a/tests/unit_tests/qpipoptmat_base.dia.ref b/tests/unit_tests/qpipoptmat_base.dia.ref
index a03fc4e..e99255c 100644
--- a/tests/unit_tests/qpipoptmat_base.dia.ref
+++ b/tests/unit_tests/qpipoptmat_base.dia.ref
@@ -69,5 +69,5 @@ ub = [%inf; %inf];
 
 assert_close ( xopt , [0.6666667 1.3333333]' , 1.e-7 );
 assert_close ( fopt , [ - 8.2222223] , 1.e-7 );
-
 assert_checkequal( exitflag , int32(0) );
+printf("Test Successful");
diff --git a/tests/unit_tests/qpipoptmat_base.tst b/tests/unit_tests/qpipoptmat_base.tst
index a03fc4e..482457d 100644
--- a/tests/unit_tests/qpipoptmat_base.tst
+++ b/tests/unit_tests/qpipoptmat_base.tst
@@ -69,5 +69,6 @@ ub = [%inf; %inf];
 
 assert_close ( xopt , [0.6666667 1.3333333]' , 1.e-7 );
 assert_close ( fopt , [ - 8.2222223] , 1.e-7 );
-
 assert_checkequal( exitflag , int32(0) );
+
+printf("Test Successfull")
diff --git a/tests/unit_tests/symphony_base.dia.ref b/tests/unit_tests/symphony_base.dia.ref
index fd11db0..64dfeea 100644
--- a/tests/unit_tests/symphony_base.dia.ref
+++ b/tests/unit_tests/symphony_base.dia.ref
@@ -83,5 +83,5 @@ status = sym_getStatus();
 
 assert_close ( x , [1 1 0 1 7.25 0 0.25 3.5] , 1.e-7 );
 assert_close ( f , [ 8495] , 1.e-7 );
-
 assert_checkequal( status , 227 );
+printf("Test Successful");
diff --git a/tests/unit_tests/symphony_base.tst b/tests/unit_tests/symphony_base.tst
index a1f9e2b..5ec76ee 100644
--- a/tests/unit_tests/symphony_base.tst
+++ b/tests/unit_tests/symphony_base.tst
@@ -80,5 +80,5 @@ isInt = [repmat(%t,1,4) repmat(%f,1,4)];
 
 assert_close ( x , [1 1 0 1 7.25 0 0.25 3.5]' , 1.e-7 );
 assert_close ( f , [ 8495] , 1.e-7 );
-
 assert_checkequal( status , 227 );
+
diff --git a/tests/unit_tests/symphonymat_base.dia.ref b/tests/unit_tests/symphonymat_base.dia.ref
index 1e6f74a..1d26663 100644
--- a/tests/unit_tests/symphonymat_base.dia.ref
+++ b/tests/unit_tests/symphonymat_base.dia.ref
@@ -79,5 +79,5 @@ status = sym_getStatus();
 
 assert_close ( x , [1 1 0 1 7.25 0 0.25 3.5] , 1.e-7 );
 assert_close ( f , [ 8495] , 1.e-7 );
-
 assert_checkequal( status , 227 );
+printf("Test Successful");
diff --git a/tests/unit_tests/symphonymat_base.tst b/tests/unit_tests/symphonymat_base.tst
index 2465738..9b32e42 100644
--- a/tests/unit_tests/symphonymat_base.tst
+++ b/tests/unit_tests/symphonymat_base.tst
@@ -76,5 +76,6 @@ intcon = [1 2 3 4];
 
 assert_close ( x , [1 1 0 1 7.25 0 0.25 3.5]' , 1.e-7 );
 assert_close ( f , [ 8495] , 1.e-7 );
-
 assert_checkequal( status , 227 );
+
+printf("Test Successfull")