qpipopt_mat added

58 files changed, 2356 insertions, 292 deletions

diff --git a/demos/qpipopt.dem.sce b/demos/qpipopt.dem.sce
index 4f20a4a..3b36ff1 100644
--- a/demos/qpipopt.dem.sce
+++ b/demos/qpipopt.dem.sce
@@ -4,40 +4,38 @@ mode(1)
 //
 
 //Find x in R^6 such that:
-halt()   // Press return to continue
- 
 conMatrix= [1,-1,1,0,3,1;
 -1,0,-3,-4,5,6;
 2,5,3,0,1,0
 0,1,0,1,2,-1;
 -1,0,2,1,1,0];
-conLB=[1 2 3 -%inf -%inf]';
-conUB = [1 2 3 -1 2.5]';
-lb=[-1000 -10000 0 -1000 -1000 -1000];
-ub=[10000 100 1.5 100 100 1000];
+conLB=[1;2;3;-%inf;-%inf];
+conUB = [1;2;3;-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
-p=[1 2 3 4 5 6]; Q=eye(6,6);
+p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6);
 nbVar = 6;
 nbCon = 5;
 [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
 halt()   // Press return to continue
  
-//min. -8*x1 -16*x2 + x1^2 + 4* x2^2
-//  such that
-//     x1 + x2 <= 5,
-//     x1 <= 3,
-//     x1 >= 0,
-//     x2 >= 0
-conMatrix= [1 1];
-conLB=[-%inf];
-conUB = [5];
-lb=[0,0];
-ub=[3,%inf];
-//and minimize 0.5*x'*Q*x + p'*x with
-p=[-8,-16];
-Q=[1,0;0,4];
+//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.
+Q = [1 -1; -1 2];
+p = [-2; -6];
+conMatrix = [1 1; -1 2; 2 1];
+conUB = [2; 2; 3];
+conLB = [-%inf; -%inf; -%inf];
+lb = [0; 0];
+ub = [%inf; %inf];
 nbVar = 2;
-nbCon = 1;
+nbCon = 3;
 [xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
 halt()   // Press return to continue
  
diff --git a/demos/qpipopt_mat.dem.sce b/demos/qpipopt_mat.dem.sce
new file mode 100644
index 0000000..0f65036
--- /dev/null
+++ b/demos/qpipopt_mat.dem.sce
@@ -0,0 +1,40 @@
+mode(1)
+//
+// Demo of qpipopt_mat.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];
+//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;
+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:
+// 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)
+halt()   // Press return to continue
+ 
+//========= E N D === O F === D E M O =========//
diff --git a/demos/symphony_knapsack.sce b/demos/symphony_knapsack.sce
index 12a6788..42c192c 100644
--- a/demos/symphony_knapsack.sce
+++ b/demos/symphony_knapsack.sce
@@ -93,7 +93,7 @@ conLB=repmat(0,nbCon,1);
 // Upper Bound of constraints
 conUB=[11927 13727 11551 13056 13460 ]';
 
-options = ["time_limit" "40"];
+options = ["tie_limit" "40"];
 
 // The expected solution :
 
diff --git a/etc/Symphony.start b/etc/Symphony.start
index 61eedbc..328357a 100644
--- a/etc/Symphony.start
+++ b/etc/Symphony.start
@@ -48,7 +48,7 @@ else
     link(lib_path + "/libSym.so");
     link(lib_path + "/libOsiSym.so");
     link(lib_path + "/libcoinblas.so");
-    link(lib_path + "/libcoinmetis.so");
+    link(lib_path + "/libcoinlapack.so");
     link(lib_path + "/libcoinmumps.so");
     link(lib_path + "/libipopt.so");
 
diff --git a/etc/Symphony.start~ b/etc/Symphony.start~
new file mode 100644
index 0000000..e019451
--- /dev/null
+++ b/etc/Symphony.start~
@@ -0,0 +1,91 @@
+// Copyright (C) 2015 - IIT Bombay - FOSSEE
+//
+// Author: Harpreet Singh
+// Organization: FOSSEE, IIT Bombay
+// Email: harpreet.mertia@gmail.com
+// This file must be used under the terms of the CeCILL.
+// This source file is licensed as described in the file COPYING, which
+// you should have received as part of this distribution.  The terms
+// are also available at
+// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
+
+mprintf("Start FAMOS\n");
+
+if ( isdef("sym_open") ) then
+        warning("Library is already loaded");
+        return;
+end
+
+etc_tlbx  = get_absolute_file_path("Symphony.start");
+etc_tlbx  = getshortpathname(etc_tlbx);
+root_tlbx = strncpy( etc_tlbx, length(etc_tlbx)-length("\etc\") );
+
+//Load  functions library
+// =============================================================================
+mprintf("\tLoad macros\n");
+pathmacros = pathconvert( root_tlbx ) + "macros" + filesep();
+symphony_lib = lib(pathmacros);
+clear pathmacros;
+
+// load gateways
+// =============================================================================
+
+mprintf("\tLoad gateways\n");
+[a, opt] = getversion();
+Version = opt(2);
+ilib_verbose(0);
+if getos()=="Windows" then
+    error(msprintf(gettext("Module is not for Windows.")));
+else
+    lib_path = root_tlbx + "/thirdparty/linux/lib/" + Version;
+    link(lib_path + "/libCoinUtils.so");
+    link(lib_path + "/libClp.so");
+    link(lib_path + "/libClpSolver.so");
+    link(lib_path + "/libOsi.so");
+    link(lib_path + "/libOsiCommonTests.so");
+    link(lib_path + "/libOsiClp.so");
+    link(lib_path + "/libCgl.so");
+    link(lib_path + "/libSym.so");
+    link(lib_path + "/libOsiSym.so");
+    link(lib_path + "/libcoinblas.so");
+    link(lib_path + "/libcoinmumps.so");
+    link(lib_path + "/libipopt.so");
+
+
+end
+exec(pathconvert(root_tlbx + filesep() + "sci_gateway" + filesep() + "loader_gateway.sce",%f));
+
+
+
+
+// Load and add help chapter
+// =============================================================================
+if ( %t ) then
+if or(getscilabmode() == ["NW";"STD"]) then
+        mprintf("\tLoad help\n");
+        path_addchapter = pathconvert(root_tlbx+"/jar");
+        if ( isdir(path_addchapter) <> [] ) then
+                add_help_chapter("Symphony", path_addchapter, %F);
+                clear add_help_chapter;
+        end
+        clear path_addchapter;
+end
+end
+
+// add demos
+// =============================================================================
+
+if ( %t ) then
+if or(getscilabmode() == ["NW";"STD"]) then
+    mprintf("\tLoad demos\n");
+    pathdemos = pathconvert(root_tlbx+"/demos/sci_symphony.dem.gateway.sce",%f,%t);
+    add_demo("Symphony",pathdemos);
+    clear pathdemos ;
+end
+end
+
+// =============================================================================
+
+clear root_tlbx;
+clear etc_tlbx;
+
diff --git a/help/en_US/master_help.xml b/help/en_US/master_help.xml
index 85ff9e0..791d3d0 100644
--- a/help/en_US/master_help.xml
+++ b/help/en_US/master_help.xml
@@ -2,6 +2,7 @@
 <!DOCTYPE book [
 <!--Begin Entities-->
 <!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 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 acc223314e8a8bc290a13618df33a6237 SYSTEM "/home/harpreet/symphony_work/symphony/help/en_US/Symphony Native Function/sym_addConstr.xml">
@@ -79,6 +80,7 @@
 <part xml:id='section_19f4f1e5726c01d683e8b82be0a7e910'>
 <title>Symphony Toolbox</title>
 &a6b85f6e0c98751f20b68663a23cb4cd2;
+&a44928acec52adf395379e18fcff06730;
 &aca972f273143ecb39f56b42e4723ac67;
 &a9953e61e8dd264a86df73772d3055e7f;
 <chapter xml:id='section_508f0b211d17ea6769714cc144e6b731'>
diff --git a/help/en_US/qpipopt.xml b/help/en_US/qpipopt.xml
index d93f758..144fe18 100644
--- a/help/en_US/qpipopt.xml
+++ b/help/en_US/qpipopt.xml
@@ -38,7 +38,7 @@
    <varlistentry><term>nbCon :</term>
       <listitem><para> a 1 x 1 matrix of doubles, number of constraints</para></listitem></varlistentry>
    <varlistentry><term>Q :</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>
+      <listitem><para> a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.</para></listitem></varlistentry>
    <varlistentry><term>p :</term>
       <listitem><para> a 1 x n matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem</para></listitem></varlistentry>
    <varlistentry><term>LB :</term>
@@ -91,19 +91,17 @@ We are calling IPOpt for solving the quadratic problem, IPOpt is a library writt
    <title>Examples</title>
    <programlisting role="example"><![CDATA[
 //Find x in R^6 such that:
-
 conMatrix= [1,-1,1,0,3,1;
 -1,0,-3,-4,5,6;
 2,5,3,0,1,0
 0,1,0,1,2,-1;
 -1,0,2,1,1,0];
-conLB=[1 2 3 -%inf -%inf]';
-conUB = [1 2 3 -1 2.5]';
-//with  x between ci and cs:
-lb=[-1000 -10000 0 -1000 -1000 -1000];
-ub=[10000 100 1.5 100 100 1000];
+conLB=[1;2;3;-%inf;-%inf];
+conUB = [1;2;3;-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
-p=[1;2;3;4;5;6]; Q=eye(6,6);
+p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6);
 nbVar = 6;
 nbCon = 5;
 [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
@@ -114,23 +112,22 @@ nbCon = 5;
 <refsection>
    <title>Examples</title>
    <programlisting role="example"><![CDATA[
-//min. -8*x1 -16*x2 + x1^2 + 4* x2^2
-//  such that
-//     x1 + x2 <= 5,
-//     x1 <= 3,
-//     x1 >= 0,
-//     x2 >= 0
-conMatrix= [1 1];
-conLB=[-%inf];
-conUB = [5];
-//with  x between ci and cs:
-lb=[0,0];
-ub=[3,%inf];
-//and minimize 0.5*x'*Q*x + p'*x with
-p=[-8,-16];
-Q=[1,0;0,4];
+//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.
+Q = [1 -1; -1 2];
+p = [-2; -6];
+conMatrix = [1 1; -1 2; 2 1];
+conUB = [2; 2; 3];
+conLB = [-%inf; -%inf; -%inf];
+lb = [0; 0];
+ub = [%inf; %inf];
 nbVar = 2;
-nbCon = 1;
+nbCon = 3;
 [xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
 
    ]]></programlisting>
diff --git a/help/en_US/qpipopt_mat.xml b/help/en_US/qpipopt_mat.xml
new file mode 100644
index 0000000..7dec2b1
--- /dev/null
+++ b/help/en_US/qpipopt_mat.xml
@@ -0,0 +1,142 @@
+<?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/scilab_en_US_help/JavaHelpSearch/DOCS b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS
index 388e399..1b55b83 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 7682874..3b7b18b 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 d55c7ec..e290f81 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 b598af6..7fd9ab2 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 60e895c..59337ab 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=1344 id2=1
+TMAP bs=2048 rt=1 fl=-1 id1=1347 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 31347cf..0f25c4d 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_qpipopt_mat.xml_1.png b/help/en_US/scilab_en_US_help/_LaTeX_qpipopt_mat.xml_1.png
new file mode 100644
index 0000000..b6e2743
--- /dev/null
+++ b/help/en_US/scilab_en_US_help/_LaTeX_qpipopt_mat.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 49a4619..2b1442a 100644
--- a/help/en_US/scilab_en_US_help/index.html
+++ b/help/en_US/scilab_en_US_help/index.html
@@ -38,6 +38,12 @@
 
 
 
+<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="symphony.html" class="refentry">symphony</a> &#8212; <span class="refentry-description">Solves a  mixed integer linear programming constrained optimization problem.</span></li>
 
 
diff --git a/help/en_US/scilab_en_US_help/jhelpmap.jhm b/help/en_US/scilab_en_US_help/jhelpmap.jhm
index 54670c0..1601f23 100644
--- a/help/en_US/scilab_en_US_help/jhelpmap.jhm
+++ b/help/en_US/scilab_en_US_help/jhelpmap.jhm
@@ -4,6 +4,7 @@
 <mapID target="index" url="index.html"/>
 <mapID target="section_19f4f1e5726c01d683e8b82be0a7e910" url="section_19f4f1e5726c01d683e8b82be0a7e910.html"/>
 <mapID target="qpipopt" url="qpipopt.html"/>
+<mapID target="qpipopt_mat" url="qpipopt_mat.html"/>
 <mapID target="symphony" url="symphony.html"/>
 <mapID target="symphony_mat" url="symphony_mat.html"/>
 <mapID target="section_508f0b211d17ea6769714cc144e6b731" url="section_508f0b211d17ea6769714cc144e6b731.html"/>
diff --git a/help/en_US/scilab_en_US_help/jhelptoc.xml b/help/en_US/scilab_en_US_help/jhelptoc.xml
index b2d66e1..463b86d 100644
--- a/help/en_US/scilab_en_US_help/jhelptoc.xml
+++ b/help/en_US/scilab_en_US_help/jhelptoc.xml
@@ -4,6 +4,7 @@
 <tocitem target="index" text="Symphony Toolbox">
 <tocitem target="section_19f4f1e5726c01d683e8b82be0a7e910" text="Symphony Toolbox">
 <tocitem target="qpipopt" text="qpipopt"/>
+<tocitem target="qpipopt_mat" text="qpipopt_mat"/>
 <tocitem target="symphony" text="symphony"/>
 <tocitem target="symphony_mat" text="symphony_mat"/>
 <tocitem target="section_508f0b211d17ea6769714cc144e6b731" text="Symphony Native Functions">
diff --git a/help/en_US/scilab_en_US_help/qpipopt.html b/help/en_US/scilab_en_US_help/qpipopt.html
index 46b56c7..fba4521 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="symphony.html">symphony &gt;&gt;</a></span>
+      	<span class="next"><a href="qpipopt_mat.html">qpipopt_mat &gt;&gt;</a></span>
 
       </td>
     </tr></table>
@@ -46,7 +46,7 @@
    <dt><span class="term">nbCon :</span>
       <dd><p class="para">a 1 x 1 matrix of doubles, number of constraints</p></dd></dt>
    <dt><span class="term">Q :</span>
-      <dd><p class="para">a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.</p></dd></dt>
+      <dd><p class="para">a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.</p></dd></dt>
    <dt><span class="term">p :</span>
       <dd><p class="para">a 1 x n matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem</p></dd></dt>
    <dt><span class="term">LB :</span>
@@ -79,41 +79,38 @@ find the minimum of f(x) such that</p>
 
 <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">conMatrix</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="scilabnumber">0</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">1</span><span class="scilabdefault">,</span><span class="scilabnumber">2</span><span class="scilabdefault">,</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="scilabdefault">,</span><span class="scilabnumber">0</span><span class="scilabdefault">,</span><span class="scilabnumber">2</span><span class="scilabdefault">,</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="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">conLB</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="scilaboperator">-</span><span class="scilabconstants">%inf</span> <span class="scilaboperator">-</span><span class="scilabconstants">%inf</span><span class="scilabopenclose">]</span><span class="scilaboperator">&#0039;</span><span class="scilabdefault">;</span>
-<span class="scilabid">conUB</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="scilaboperator">-</span><span class="scilabnumber">1</span> <span class="scilabnumber">2.5</span><span class="scilabopenclose">]</span><span class="scilaboperator">&#0039;</span><span class="scilabdefault">;</span>
-<span class="scilabcomment">//with  x between ci and cs:</span>
-<span class="scilabid">lb</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilaboperator">-</span><span class="scilabnumber">1000</span> <span class="scilaboperator">-</span><span class="scilabnumber">10000</span> <span class="scilabnumber">0</span> <span class="scilaboperator">-</span><span class="scilabnumber">1000</span> <span class="scilaboperator">-</span><span class="scilabnumber">1000</span> <span class="scilaboperator">-</span><span class="scilabnumber">1000</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">ub</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilabnumber">10000</span> <span class="scilabnumber">100</span> <span class="scilabnumber">1.5</span> <span class="scilabnumber">100</span> <span class="scilabnumber">100</span> <span class="scilabnumber">1000</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">conLB</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="scilaboperator">-</span><span class="scilabconstants">%inf</span><span class="scilabdefault">;</span><span class="scilaboperator">-</span><span class="scilabconstants">%inf</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">conUB</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="scilaboperator">-</span><span class="scilabnumber">1</span><span class="scilabdefault">;</span><span class="scilabnumber">2.5</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">lb</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilaboperator">-</span><span class="scilabnumber">1000</span><span class="scilabdefault">;</span><span class="scilaboperator">-</span><span class="scilabnumber">10000</span><span class="scilabdefault">;</span> <span class="scilabnumber">0</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">1000</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">1000</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">1000</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">ub</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilabnumber">10000</span><span class="scilabdefault">;</span> <span class="scilabnumber">100</span><span class="scilabdefault">;</span> <span class="scilabnumber">1.5</span><span class="scilabdefault">;</span> <span class="scilabnumber">100</span><span class="scilabdefault">;</span> <span class="scilabnumber">100</span><span class="scilabdefault">;</span> <span class="scilabnumber">1000</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">p</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">Q</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="scilabid">p</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">Q</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="scilabid">nbVar</span> <span class="scilaboperator">=</span> <span class="scilabnumber">6</span><span class="scilabdefault">;</span>
 <span class="scilabid">nbCon</span> <span class="scilaboperator">=</span> <span class="scilabnumber">5</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="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">Examples</h3>
-   <div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabcomment">//min. -8*x1 -16*x2 + x1^2 + 4* x2^2</span>
-<span class="scilabcomment">//  such that</span>
-<span class="scilabcomment">//     x1 + x2 </span><span class="scilabcomment">&#0060;</span><span class="scilabcomment">= 5,</span>
-<span class="scilabcomment">//     x1 </span><span class="scilabcomment">&#0060;</span><span class="scilabcomment">= 3,</span>
-<span class="scilabcomment">//     x1 </span><span class="scilabcomment">&#0062;</span><span class="scilabcomment">= 0,</span>
-<span class="scilabcomment">//     x2 </span><span class="scilabcomment">&#0062;</span><span class="scilabcomment">= 0</span>
-<span class="scilabid">conMatrix</span><span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">1</span> <span class="scilabnumber">1</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">conLB</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilaboperator">-</span><span class="scilabconstants">%inf</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">conUB</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">5</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabcomment">//with  x between ci and cs:</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="scilabnumber">3</span><span class="scilabdefault">,</span><span class="scilabconstants">%inf</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">p</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilaboperator">-</span><span class="scilabnumber">8</span><span class="scilabdefault">,</span><span class="scilaboperator">-</span><span class="scilabnumber">16</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
-<span class="scilabid">Q</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilabnumber">0</span><span class="scilabdefault">;</span><span class="scilabnumber">0</span><span class="scilabdefault">,</span><span class="scilabnumber">4</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</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">Q</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">p</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">conMatrix</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">conUB</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">conLB</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilaboperator">-</span><span class="scilabconstants">%inf</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabconstants">%inf</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabconstants">%inf</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="scilabid">nbVar</span> <span class="scilaboperator">=</span> <span class="scilabnumber">2</span><span class="scilabdefault">;</span>
-<span class="scilabid">nbCon</span> <span class="scilaboperator">=</span> <span class="scilabnumber">1</span><span class="scilabdefault">;</span>
+<span class="scilabid">nbCon</span> <span class="scilaboperator">=</span> <span class="scilabnumber">3</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="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>
@@ -133,7 +130,7 @@ find the minimum of f(x) such that</p>
 
       </td>
       <td width="30%" class="next">
-      	<span class="next"><a href="symphony.html">symphony &gt;&gt;</a></span>
+      	<span class="next"><a href="qpipopt_mat.html">qpipopt_mat &gt;&gt;</a></span>
 
       </td>
     </tr></table>
diff --git a/help/en_US/scilab_en_US_help/qpipopt_mat.html b/help/en_US/scilab_en_US_help/qpipopt_mat.html
new file mode 100644
index 0000000..5e30769
--- /dev/null
+++ b/help/en_US/scilab_en_US_help/qpipopt_mat.html
@@ -0,0 +1,139 @@
+<html><head>
+    <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
+    <title>qpipopt_mat</title>
+    <style type="text/css" media="all">
+      @import url("scilab_code.css");
+      @import url("xml_code.css");
+      @import url("c_code.css");
+      @import url("style.css");
+    </style>
+  </head>
+  <body>
+    <div class="manualnavbar">
+    <table width="100%"><tr>
+      <td width="30%">
+    	<span class="previous"><a href="qpipopt.html">&lt;&lt; qpipopt</a></span>
+
+      </td>
+      <td width="40%" class="center">
+      	<span class="top"><a href="section_19f4f1e5726c01d683e8b82be0a7e910.html">Symphony Toolbox</a></span>
+
+      </td>
+      <td width="30%" class="next">
+      	<span class="next"><a href="symphony.html">symphony &gt;&gt;</a></span>
+
+      </td>
+    </tr></table>
+      <hr />
+    </div>
+
+
+
+    <span class="path"><a href="index.html">Symphony Toolbox</a> &gt;&gt; <a href="section_19f4f1e5726c01d683e8b82be0a7e910.html">Symphony Toolbox</a> &gt; qpipopt_mat</span>
+
+    <br /><br />
+    <div class="refnamediv"><h1 class="refname">qpipopt_mat</h1>
+    <p class="refpurpose">Solves a linear quadratic problem.</p></div>
+
+
+<div class="refsynopsisdiv"><h3 class="title">Calling Sequence</h3>
+   <div class="synopsis"><pre><span class="default">xopt</span><span class="default"> = </span><span class="functionid">qpipopt_mat</span><span class="default">(</span><span class="default">nbVar</span><span class="default">,</span><span class="default">nbCon</span><span class="default">,</span><span class="default">Q</span><span class="default">,</span><span class="default">p</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">conMatrix</span><span class="default">,</span><span class="default">conLB</span><span class="default">,</span><span class="default">conUB</span><span class="default">)</span>
+<span class="default">x</span><span class="default"> = </span><span class="functionid">qpipopt_mat</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">qpipopt_mat</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">qpipopt_mat</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">qpipopt_mat</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">[</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">qpipopt_mat</span><span class="default">( ... )</span></pre></div></div>
+
+<div class="refsection"><h3 class="title">Parameters</h3>
+   <dl><dt><span class="term">H :</span>
+      <dd><p class="para">a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.</p></dd></dt>
+   <dt><span class="term">f :</span>
+      <dd><p class="para">a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem</p></dd></dt>
+   <dt><span class="term">A :</span>
+      <dd><p class="para">a m x n matrix of doubles, represents the linear coefficients in the inequality constraints</p></dd></dt>
+   <dt><span class="term">b :</span>
+      <dd><p class="para">a column vector of doubles, represents the linear coefficients in the inequality constraints</p></dd></dt>
+   <dt><span class="term">Aeq :</span>
+      <dd><p class="para">a meq x n matrix of doubles, represents the linear coefficients in the equality constraints</p></dd></dt>
+   <dt><span class="term">beq :</span>
+      <dd><p class="para">a vector of doubles, represents the linear coefficients in the equality constraints</p></dd></dt>
+   <dt><span class="term">LB :</span>
+      <dd><p class="para">a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.</p></dd></dt>
+   <dt><span class="term">UB :</span>
+      <dd><p class="para">a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.</p></dd></dt>
+   <dt><span class="term">xopt :</span>
+      <dd><p class="para">a nx1 matrix of doubles, the computed solution of the optimization problem.</p></dd></dt>
+   <dt><span class="term">fopt :</span>
+      <dd><p class="para">a 1x1 matrix of doubles, the function value at x.</p></dd></dt>
+   <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>
+   <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>
+
+<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_mat.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"></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>
+
+<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>
+<span class="scilabid">beq</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="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">A</span><span class="scilaboperator">=</span> <span class="scilabopenclose">[</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="scilabdefault">,</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilabnumber">2</span><span class="scilabdefault">,</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="scilabdefault">,</span><span class="scilabnumber">0</span><span class="scilabdefault">,</span><span class="scilabnumber">2</span><span class="scilabdefault">,</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="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">b</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilaboperator">-</span><span class="scilabnumber">1</span><span class="scilabdefault">;</span> <span class="scilabnumber">2.5</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">lb</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilaboperator">-</span><span class="scilabnumber">1000</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">10000</span><span class="scilabdefault">;</span> <span class="scilabnumber">0</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">1000</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">1000</span><span class="scilabdefault">;</span> <span class="scilaboperator">-</span><span class="scilabnumber">1000</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
+<span class="scilabid">ub</span><span class="scilaboperator">=</span><span class="scilabopenclose">[</span><span class="scilabnumber">10000</span><span class="scilabdefault">;</span> <span class="scilabnumber">100</span><span class="scilabdefault">;</span> <span class="scilabnumber">1.5</span><span class="scilabdefault">;</span> <span class="scilabnumber">100</span><span class="scilabdefault">;</span> <span class="scilabnumber">100</span><span class="scilabdefault">;</span> <span class="scilabnumber">1000</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">qpipopt_mat</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="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">qpipopt_mat</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>
+
+<div class="refsection"><h3 class="title">Authors</h3>
+   <ul class="itemizedlist"><li class="member">Keyur Joshi, Saikiran, Iswarya, Harpreet Singh</li></ul></div>
+    <br />
+
+    <div class="manualnavbar">
+    <table width="100%">
+    <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.html">&lt;&lt; qpipopt</a></span>
+
+      </td>
+      <td width="40%" class="center">
+      	<span class="top"><a href="section_19f4f1e5726c01d683e8b82be0a7e910.html">Symphony Toolbox</a></span>
+
+      </td>
+      <td width="30%" class="next">
+      	<span class="next"><a href="symphony.html">symphony &gt;&gt;</a></span>
+
+      </td>
+    </tr></table>
+      <hr />
+    </div>
+  </body>
+</html>
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 0f8d441..ed07ab6 100644
--- a/help/en_US/scilab_en_US_help/section_19f4f1e5726c01d683e8b82be0a7e910.html
+++ b/help/en_US/scilab_en_US_help/section_19f4f1e5726c01d683e8b82be0a7e910.html
@@ -37,6 +37,12 @@
 
 
 
+<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="symphony.html" class="refentry">symphony</a> &#8212; <span class="refentry-description">Solves a  mixed integer linear programming constrained optimization problem.</span></li>
 
 
diff --git a/help/en_US/scilab_en_US_help/symphony.html b/help/en_US/scilab_en_US_help/symphony.html
index 7e155bc..0af9d1b 100644
--- a/help/en_US/scilab_en_US_help/symphony.html
+++ b/help/en_US/scilab_en_US_help/symphony.html
@@ -12,7 +12,7 @@
     <div class="manualnavbar">
     <table width="100%"><tr>
       <td width="30%">
-    	<span class="previous"><a href="qpipopt.html">&lt;&lt; qpipopt</a></span>
+    	<span class="previous"><a href="qpipopt_mat.html">&lt;&lt; qpipopt_mat</a></span>
 
       </td>
       <td width="40%" class="center">
@@ -197,7 +197,7 @@ 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="qpipopt.html">&lt;&lt; qpipopt</a></span>
+    	<span class="previous"><a href="qpipopt_mat.html">&lt;&lt; qpipopt_mat</a></span>
 
       </td>
       <td width="40%" class="center">
diff --git a/hs_err_pid20719.log b/hs_err_pid20719.log
new file mode 100644
index 0000000..c1efcc0
--- /dev/null
+++ b/hs_err_pid20719.log
@@ -0,0 +1,173 @@
+#
+# A fatal error has been detected by the Java Runtime Environment:
+#
+#  SIGSEGV (0xb) at pc=0x0000000000000020, pid=20719, tid=140693220591488
+#
+# JRE version: OpenJDK Runtime Environment (7.0_79-b14) (build 1.7.0_79-b14)
+# Java VM: OpenJDK 64-Bit Server VM (24.79-b02 mixed mode linux-amd64 compressed oops)
+# Derivative: IcedTea 2.5.6
+# Distribution: Ubuntu 14.04 LTS, package 7u79-2.5.6-0ubuntu1.14.04.1
+# Problematic frame:
+# C  0x0000000000000020
+#
+# Failed to write core dump. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again
+#
+# If you would like to submit a bug report, please include
+# instructions on how to reproduce the bug and visit:
+#   http://icedtea.classpath.org/bugzilla
+# The crash happened outside the Java Virtual Machine in native code.
+# See problematic frame for where to report the bug.
+#
+
+---------------  T H R E A D  ---------------
+
+Current thread (0x000000000093d800):  JavaThread "main" [_thread_in_native, id=20719, stack(0x00007fffa831b000,0x00007fffa841b000)]
+
+siginfo:si_signo=SIGSEGV: si_errno=0, si_code=1 (SEGV_MAPERR), si_addr=0x0000000000000020
+
+Registers:
+RAX=0x0000000000001000, RBX=0x000000000112b5f0, RCX=0x00007ff5a652282d, RDX=0x0000000000001000
+RSP=0x00007fffa84180f0, RBP=0x0000000000000000, RSI=0x00007ff544005000, RDI=0x0000000000000000
+R8 =0x0000000000001000, R9 =0x00007fffa841823c, R10=0x0000000000000022, R11=0x0000000000000000
+R12=0x0000000000000004, R13=0x0000000000000004, R14=0x00007fffa841823c, R15=0x0000000000000001
+RIP=0x0000000000000020, EFLAGS=0x0000000000010217, CSGSFS=0x0000000000000033, ERR=0x0000000000000014
+  TRAPNO=0x000000000000000e
+
+Top of Stack: (sp=0x00007fffa84180f0)
+0x00007fffa84180f0:   000000000000000b 0000000000000001
+0x00007fffa8418100:   00007fffa84385b0 00007ff5a64b0498
+0x00007fffa8418110:   ffff88012ed93e80 0000000000000000
+0x00007fffa8418120:   0000000000000004 0000000000000001
+0x00007fffa8418130:   00007fffa8418230 00007ff5a64a593f
+0x00007fffa8418140:   0000000000000fd9 00007fffa841823c
+0x00007fffa8418150:   00007ff5ae66d288 00007ff5ae40da8d
+0x00007fffa8418160:   000000000112b5f0 00007ff5ae0b00c3
+0x00007fffa8418170:   00007fffa8418230 000000000000003a
+0x00007fffa8418180:   000000000000037f 00007ff5b05ef0c0
+0x00007fffa8418190:   00007ff5b0596280 0002ffff00001fa0
+0x00007fffa84181a0:   0000000000000000 0000000000000000
+0x00007fffa84181b0:   0000000000000000 0000000000000000
+0x00007fffa84181c0:   0000000000000000 0000000000000000
+0x00007fffa84181d0:   0000000000000000 0000000000000000
+0x00007fffa84181e0:   0000000000000000 0000000000000000
+0x00007fffa84181f0:   0000000000000000 0000000000000000
+0x00007fffa8418200:   0000000000000000 0000000000000000
+0x00007fffa8418210:   0000000000000000 0000000000000000
+0x00007fffa8418220:   00000000000000ff 00000000000000ff
+0x00007fffa8418230:   2525252525252525 2525252525252525
+0x00007fffa8418240:   6f7272652d2d2120 2020203939392072
+0x00007fffa8418250:   0000000000000000 0000000000000000
+0x00007fffa8418260:   00000000000000ff 00000000000000ff
+0x00007fffa8418270:   000000003717f7d1 0000000000000000
+0x00007fffa8418280:   00000000bcc8d589 0000000000000000
+0x00007fffa8418290:   0000000000000000 0000000000000000
+0x00007fffa84182a0:   0000000000ff0000 0000000000000000
+0x00007fffa84182b0:   0000000000000000 0000ff0000000000
+0x00007fffa84182c0:   0000000000000000 ff00000000000000
+0x00007fffa84182d0:   0000ff0000000000 0000000000000000
+0x00007fffa84182e0:   0000000000ff0000 0000000000000000 
+
+Instructions: (pc=0x0000000000000020)
+0x0000000000000000:   
+[error occurred during error reporting (printing registers, top of stack, instructions near pc), id 0xb]
+
+Register to memory mapping:
+
+RAX=0x0000000000001000 is an unknown value
+RBX=0x000000000112b5f0 is an unknown value
+RCX=0x00007ff5a652282d: __read+0x2d in /lib/x86_64-linux-gnu/libc.so.6 at 0x00007ff5a6437000
+RDX=0x0000000000001000 is an unknown value
+RSP=0x00007fffa84180f0 is pointing into the stack for thread: 0x000000000093d800
+RBP=0x0000000000000000 is an unknown value
+RSI=0x00007ff544005000 is an unknown value
+RDI=0x0000000000000000 is an unknown value
+R8 =0x0000000000001000 is an unknown value
+R9 =0x00007fffa841823c is pointing into the stack for thread: 0x000000000093d800
+R10=0x0000000000000022 is an unknown value
+R11=0x0000000000000000 is an unknown value
+R12=0x0000000000000004 is an unknown value
+R13=0x0000000000000004 is an unknown value
+R14=0x00007fffa841823c is pointing into the stack for thread: 0x000000000093d800
+R15=0x0000000000000001 is an unknown value
+
+
+Stack: [0x00007fffa831b000,0x00007fffa841b000],  sp=0x00007fffa84180f0,  free space=1012k
+Native frames: (J=compiled Java code, j=interpreted, Vv=VM code, C=native code)
+C  0x0000000000000020
+
+[error occurred during error reporting (printing native stack), id 0xb]
+
+
+---------------  P R O C E S S  ---------------
+
+Java Threads: ( => current thread )
+  0x0000000000e4f800 JavaThread "main-SharedResourceRunner" daemon [_thread_blocked, id=20736, stack(0x00007ff5915c7000,0x00007ff5916c8000)]
+  0x0000000000d12000 JavaThread "AWT-XAWT" daemon [_thread_in_vm, id=20733, stack(0x00007ff592783000,0x00007ff592884000)]
+  0x0000000000cfa000 JavaThread "Java2D Disposer" daemon [_thread_blocked, id=20732, stack(0x00007ff592c94000,0x00007ff592d95000)]
+  0x0000000000a23800 JavaThread "Service Thread" daemon [_thread_blocked, id=20730, stack(0x00007ff599c9d000,0x00007ff599d9e000)]
+  0x0000000000a21800 JavaThread "C2 CompilerThread1" daemon [_thread_blocked, id=20729, stack(0x00007ff599d9e000,0x00007ff599e9f000)]
+  0x0000000000a1e800 JavaThread "C2 CompilerThread0" daemon [_thread_blocked, id=20728, stack(0x00007ff599e9f000,0x00007ff599fa0000)]
+  0x0000000000a1c800 JavaThread "Attach Listener" daemon [_thread_blocked, id=20727, stack(0x00007ff599fa0000,0x00007ff59a0a1000)]
+  0x00000000009f2800 JavaThread "Finalizer" daemon [_thread_blocked, id=20726, stack(0x00007ff59a0a1000,0x00007ff59a1a2000)]
+  0x00000000009f0800 JavaThread "Reference Handler" daemon [_thread_blocked, id=20725, stack(0x00007ff59a1a2000,0x00007ff59a2a3000)]
+=>0x000000000093d800 JavaThread "main" [_thread_in_native, id=20719, stack(0x00007fffa831b000,0x00007fffa841b000)]
+
+Other Threads:
+  0x00000000009ec000 VMThread [stack: 0x00007ff59a2a3000,0x00007ff59a3a4000] [id=20724]
+  0x0000000000a2e800 WatcherThread [stack: 0x00007ff599b9c000,0x00007ff599c9d000] [id=20731]
+
+VM state:not at safepoint (normal execution)
+
+VM Mutex/Monitor currently owned by a thread: None
+
+Heap
+ PSYoungGen      total 62464K, used 16672K [0x00000000faa80000, 0x0000000100000000, 0x0000000100000000)
+  eden space 54272K, 19% used [0x00000000faa80000,0x00000000fb4e6e88,0x00000000fdf80000)
+  from space 8192K, 73% used [0x00000000fdf80000,0x00000000fe5612c0,0x00000000fe780000)
+  to   space 8704K, 0% used [0x00000000ff780000,0x00000000ff780000,0x0000000100000000)
+ ParOldGen       total 35328K, used 10290K [0x00000000f0000000, 0x00000000f2280000, 0x00000000faa80000)
+  object space 35328K, 29% used [0x00000000f0000000,0x00000000f0a0cbd0,0x00000000f2280000)
+ PSPermGen       total 24064K, used 23724K [0x00000000e5a00000, 0x00000000e7180000, 0x00000000f0000000)
+  object space 24064K, 98% used [0x00000000e5a00000,0x00000000e712b1f8,0x00000000e7180000)
+
+Card table byte_map: [0x00007ff5b1563000,0x00007ff5b1637000] byte_map_base: 0x00007ff5b0e36000
+
+Polling page: 0x00007ff5b173d000
+
+Code Cache  [0x00007ff59bad0000, 0x00007ff59bd40000, 0x00007ff59ead0000)
+ total_blobs=1355 nmethods=500 adapters=809 free_code_cache=47022Kb largest_free_block=48093248
+
+Compilation events (10 events):
+Event: 8180.565 Thread 0x0000000000a21800  520             java.util.concurrent.locks.AbstractOwnableSynchronizer::getExclusiveOwnerThread (5 bytes)
+Event: 8180.566 Thread 0x0000000000a21800 nmethod 520 0x00007ff59bc1d450 code [0x00007ff59bc1d580, 0x00007ff59bc1d5d8]
+Event: 8233.641 Thread 0x0000000000a1e800  521             java.util.concurrent.locks.AbstractQueuedSynchronizer::setState (6 bytes)
+Event: 8233.642 Thread 0x0000000000a1e800 nmethod 521 0x00007ff59bce8690 code [0x00007ff59bce87c0, 0x00007ff59bce8818]
+Event: 8520.046 Thread 0x0000000000a21800  522             java.util.concurrent.locks.AbstractQueuedSynchronizer::compareAndSetState (13 bytes)
+Event: 8520.047 Thread 0x0000000000a21800 nmethod 522 0x00007ff59bce8490 code [0x00007ff59bce85c0, 0x00007ff59bce8618]
+Event: 8520.547 Thread 0x0000000000a1e800  523             java.util.concurrent.locks.AbstractQueuedSynchronizer::release (33 bytes)
+Event: 8520.551 Thread 0x0000000000a1e800 nmethod 523 0x00007ff59bc4a550 code [0x00007ff59bc4a6a0, 0x00007ff59bc4a788]
+Event: 8522.049 Thread 0x0000000000a21800  524             java.util.concurrent.locks.ReentrantLock::unlock (10 bytes)
+Event: 8522.054 Thread 0x0000000000a21800 nmethod 524 0x00007ff59bc4a210 code [0x00007ff59bc4a360, 0x00007ff59bc4a448]
+
+GC Heap History (10 events):
+Event: 3.643 GC heap before
+{Heap before GC invocations=3 (full 0):
+ PSYoungGen      total 15872K, used 15840K [0x00000000faa80000, 0x00000000fc980000, 0x0000000100000000)
+  eden space 13824K, 100% used [0x00000000faa80000,0x00000000fb800000,0x00000000fb800000)
+  from space 2048K, 98% used [0x00000000fba00000,0x00000000fbbf8020,0x00000000fbc00000)
+  to   space 2048K, 0% used [0x00000000fb800000,0x00000000fb800000,0x00000000fba00000)
+ ParOldGen       total 35328K, used 3941K [0x00000000f0000000, 0x00000000f2280000, 0x00000000faa80000)
+  object space 35328K, 11% used [0x00000000f0000000,0x00000000f03d96d8,0x00000000f2280000)
+ PSPermGen       total 21504K, used 17695K [0x00000000e5a00000, 0x00000000e6f00000, 0x00000000f0000000)
+  object space 21504K, 82% used [0x00000000e5a00000,0x00000000e6b47ef8,0x00000000e6f00000)
+Event: 3.667 GC heap after
+Heap after GC invocations=3 (full 0):
+ PSYoungGen      total 15872K, used 2016K [0x00000000faa80000, 0x00000000fc980000, 0x0000000100000000)
+  eden space 13824K, 0% used [0x00000000faa80000,0x00000000faa80000,0x00000000fb800000)
+  from space 2048K, 98% used [0x00000000fb800000,0x00000000fb9f8020,0x00000000fba00000)
+  to   space 2048K, 0% used [0x00000000fc780000,0x00000000fc780000,0x00000000fc980000)
+ ParOldGen       total 35328K, used 4411K [0x00000000f0000000, 0x00000000f2280000, 0x00000000faa80000)
+  object space 35328K, 12% used [0x00000000f0000000,0x00000000f044efd8,0x00000000f2280000)
+ PSPermGen       total 21504K, used 17695K [0x00000000e5a00000, 0x00000000e6f00000, 0x00000000f0000000)
+  object space 21504K, 82% used [0x00000000e5a00000,0x00000000e6b47ef8,0x00000000e6f00000)
+}
diff --git a/jar/scilab_en_US_help.jar b/jar/scilab_en_US_help.jar
index 51f187b..61cfd75 100644
--- a/jar/scilab_en_US_help.jar
+++ b/jar/scilab_en_US_help.jar
diff --git a/macros/lib b/macros/lib
index ba55302..3569a7d 100644
--- a/macros/lib
+++ b/macros/lib
diff --git a/macros/names b/macros/names
index da92859..ef678fc 100644
--- a/macros/names
+++ b/macros/names
@@ -1,4 +1,5 @@
 qpipopt
+qpipopt_mat
 setOptions
 symphony
 symphony_call
diff --git a/macros/qpipopt.bin b/macros/qpipopt.bin
index 594d645..757b5b6 100644
--- a/macros/qpipopt.bin
+++ b/macros/qpipopt.bin
diff --git a/macros/qpipopt.sci b/macros/qpipopt.sci
index 0d1b6b6..4f8c535 100644
--- a/macros/qpipopt.sci
+++ b/macros/qpipopt.sci
@@ -20,7 +20,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //   Parameters
   //   nbVar : a 1 x 1 matrix of doubles, number of variables
   //   nbCon : a 1 x 1 matrix of doubles, number of constraints
-  //   Q : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
+  //   Q : a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
   //   p : a 1 x n matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem
   //   LB : a 1 x n matrix of doubles, where n is number of variables, contains lower bounds of the variables.
   //   UB : a 1 x n matrix of doubles, where n is number of variables, contains upper bounds of the variables.
@@ -50,42 +50,39 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //
   // Examples
   //      //Find x in R^6 such that:
-  //      
   //      conMatrix= [1,-1,1,0,3,1;
   //                 -1,0,-3,-4,5,6;
   //                  2,5,3,0,1,0
   //                  0,1,0,1,2,-1;
   //                 -1,0,2,1,1,0];
-  //      conLB=[1 2 3 -%inf -%inf]';
-  //      conUB = [1 2 3 -1 2.5]';
-  //      //with  x between ci and cs:
-  //      lb=[-1000 -10000 0 -1000 -1000 -1000];
-  //      ub=[10000 100 1.5 100 100 1000];
+  //      conLB=[1;2;3;-%inf;-%inf];
+  //      conUB = [1;2;3;-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
-  //      p=[1 2 3 4 5 6]; Q=eye(6,6);
+  //      p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6);
   //      nbVar = 6;
   //      nbCon = 5;
   //      [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
   //    
   // Examples 
-  //      //min. -8*x1 -16*x2 + x1^2 + 4* x2^2
-  //      //  such that
-  //      //     x1 + x2 <= 5,
-  //      //     x1 <= 3,
-  //      //     x1 >= 0,
-  //      //     x2 >= 0
-  //      conMatrix= [1 1];
-  //      conLB=[-%inf];
-  //      conUB = [5];
-  //      //with  x between ci and cs:
-  //      lb=[0,0];
-  //      ub=[3,%inf];
-  //      //and minimize 0.5*x'*Q*x + p'*x with
-  //      p=[-8,-16]; 
-  //      Q=[1,0;0,4];
-  //      nbVar = 2;
-  //      nbCon = 1;
-  //      [xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
+  //    //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.
+  //	Q = [1 -1; -1 2]; 
+  //	p = [-2; -6];
+  //    conMatrix = [1 1; -1 2; 2 1];
+  //	conUB = [2; 2; 3];
+  //	conLB = [-%inf; -%inf; -%inf];
+  //	lb = [0; 0];
+  //	ub = [%inf; %inf];
+  //	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
@@ -109,10 +106,21 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
    UB = varargin(6);
    conMatrix = varargin(7);
    conLB = varargin(8);
-   conLB = conLB';  //IPOpt wants it in row matrix form 
    conUB = varargin(9);
-   conUB = conUB';	//IPOpt wants it in row matrix form
    
+   //IPOpt wants it in row matrix form
+   p = p';
+   LB = LB';
+   UB = UB';
+   conLB = conLB';
+   conUB = conUB';
+   
+   //Checking the Q matrix which needs to be a symmetric matrix
+   if ( Q~=Q') then
+      errmsg = msprintf(gettext("%s: Q is not a symmetric matrix"), "qpipopt");
+      error(errmsg);
+   end
+
    //Check the size of Q which should equal to the number of variable
    if ( size(Q) ~= [nbVar nbVar]) then
       errmsg = msprintf(gettext("%s: The Size of Q is not equal to the number of variables"), "qpipopt");
@@ -126,31 +134,31 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
    end
    
    
-//Check the size of constraint which should equal to the number of constraints
-   if ( size(conMatrix,1) ~= nbCon) then
-      errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt");
+   //Check the size of constraint which should equal to the number of variables
+   if ( size(conMatrix,2) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The size of constraints is not equal to the number of variables"), "qpipopt");
       error(errmsg);
    end
 
-//Check the size of Lower Bound which should equal to the number of variables
+   //Check the size of Lower Bound which should equal to the number of variables
    if ( size(LB,2) ~= nbVar) then
       errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt");
       error(errmsg);
    end
 
-//Check the size of Upper Bound which should equal to the number of variables
+   //Check the size of Upper Bound which should equal to the number of variables
    if ( size(UB,2) ~= nbVar) then
       errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipopt");
       error(errmsg);
    end
 
-//Check the size of constraints of Lower Bound which should equal to the number of constraints
+   //Check the size of constraints of Lower Bound which should equal to the number of constraints
    if ( size(conLB,2) ~= nbCon) then
       errmsg = msprintf(gettext("%s: The Lower Bound of constraints is not equal to the number of constraints"), "qpipopt");
       error(errmsg);
    end
 
-//Check the size of constraints of Upper Bound which should equal to the number of constraints
+   //Check the size of constraints of Upper Bound which should equal to the number of constraints
    if ( size(conUB,2) ~= nbCon) then
       errmsg = msprintf(gettext("%s: The Upper Bound of constraints is not equal to the number of constraints"), "qp_ipopt");
       error(errmsg);
diff --git a/macros/qpipopt.sci~ b/macros/qpipopt.sci~
new file mode 100644
index 0000000..407a6b7
--- /dev/null
+++ b/macros/qpipopt.sci~
@@ -0,0 +1,172 @@
+// Copyright (C) 2015 - IIT Bombay - FOSSEE
+//
+// Author: Harpreet Singh
+// Organization: FOSSEE, IIT Bombay
+// Email: harpreet.mertia@gmail.com
+// This file must be used under the terms of the CeCILL.
+// This source file is licensed as described in the file COPYING, which
+// you should have received as part of this distribution.  The terms
+// are also available at
+// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
+
+
+function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
+  // Solves a linear quadratic problem.
+  //
+  //   Calling Sequence
+  //   xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB)
+  //   [xopt,fopt,exitflag,output,lamda] = qpipopt( ... )
+  //   
+  //   Parameters
+  //   nbVar : a 1 x 1 matrix of doubles, number of variables
+  //   nbCon : a 1 x 1 matrix of doubles, number of constraints
+  //   Q : a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
+  //   p : a 1 x n matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem
+  //   LB : a 1 x n matrix of doubles, where n is number of variables, contains lower bounds of the variables.
+  //   UB : a 1 x n matrix of doubles, where n is number of variables, contains upper bounds of the variables.
+  //   conMatrix : a m x n matrix of doubles, where n is number of variables and m is number of constraints, contains  matrix representing the constraint matrix 
+  //   conLB : a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints. 
+  //   conUB : a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints.
+  //   xopt : a 1xn matrix of doubles, the computed solution of the optimization problem.
+  //   fopt : a 1x1 matrix of doubles, 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'*Q*x + p'*x  \\
+  //    & \text{subject to} & conLB \leq C(x) \leq conUB \\
+  //    & & 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:
+  //      
+  //      conMatrix= [1,-1,1,0,3,1;
+  //                 -1,0,-3,-4,5,6;
+  //                  2,5,3,0,1,0
+  //                  0,1,0,1,2,-1;
+  //                 -1,0,2,1,1,0];
+  //      conLB=[1;2;3;-%inf;-%inf];
+  //      conUB = [1;2;3;-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
+  //      p=[1 2 3 4 5 6]; Q=eye(6,6);
+  //      nbVar = 6;
+  //      nbCon = 5;
+  //      [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
+  //    
+  // Examples 
+  //	Q = [1 -1; -1 2]; 
+  //	p = [-2 -6];
+  //	conMatrix = [1 1; -1 2; 2 1];
+  //	conUB = [2; 2; 3];
+  //	conLB = [-%inf; -%inf; -%inf];
+  //	lb = [0 0];
+  //	ub = [%inf %inf];
+  //	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
+    
+    
+//To check the number of input and output argument
+   [lhs , rhs] = argn();
+	
+//To check the number of argument given by user
+   if ( rhs ~= 9 ) then
+    errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9"), "qpipopt", rhs);
+    error(errmsg)
+   end
+   
+   
+   nbVar = varargin(1);
+   nbCon = varargin(2);
+   Q = varargin(3);
+   p = varargin(4);
+   LB = varargin(5);
+   UB = varargin(6);
+   conMatrix = varargin(7);
+   conLB = varargin(8);
+   conLB = conLB';	//IPOpt wants it in row matrix form 
+   conUB = varargin(9);
+   conUB = conUB';	//IPOpt wants it in row matrix form
+   
+
+   //Checking the Q matrix which needs to be a symmetric matrix
+   if ( Q~=Q') then
+      errmsg = msprintf(gettext("%s: Q is not a symmetric matrix"), "qpipopt");
+      error(errmsg);
+   end
+
+   //Check the size of Q which should equal to the number of variable
+   if ( size(Q) ~= [nbVar nbVar]) then
+      errmsg = msprintf(gettext("%s: The Size of Q is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+   
+   //Check the size of p which should equal to the number of variable
+   if ( size(p,2) ~= [nbVar]) then
+      errmsg = msprintf(gettext("%s: The Size of p is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+   
+   
+   //Check the size of constraint which should equal to the number of variables
+   if ( size(conMatrix,2) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The size of constraints is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+   //Check the size of Lower Bound which should equal to the number of variables
+   if ( size(LB,2) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+   //Check the size of Upper Bound which should equal to the number of variables
+   if ( size(UB,2) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+   //Check the size of constraints of Lower Bound which should equal to the number of constraints
+   if ( size(conLB,2) ~= nbCon) then
+      errmsg = msprintf(gettext("%s: The Lower Bound of constraints is not equal to the number of constraints"), "qpipopt");
+      error(errmsg);
+   end
+
+   //Check the size of constraints of Upper Bound which should equal to the number of constraints
+   if ( size(conUB,2) ~= nbCon) then
+      errmsg = msprintf(gettext("%s: The Upper Bound of constraints is not equal to the number of constraints"), "qp_ipopt");
+      error(errmsg);
+   end
+    
+   [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB);
+   
+   xopt = xopt';
+   exitflag = status;
+   output = struct("Iterations"      , []);
+   output.Iterations = iter;
+   lambda = struct("lower"           , [], ..
+                   "upper"           , [], ..
+                   "constraint"      , []);
+   
+   lambda.lower = Zl;
+   lambda.upper = Zu;
+   lambda.constraint = lmbda;
+    
+
+endfunction
diff --git a/macros/qpipopt_mat.bin b/macros/qpipopt_mat.bin
new file mode 100644
index 0000000..43cce6e
--- /dev/null
+++ b/macros/qpipopt_mat.bin
diff --git a/macros/qpipopt_mat.sci b/macros/qpipopt_mat.sci
new file mode 100644
index 0000000..4c72216
--- /dev/null
+++ b/macros/qpipopt_mat.sci
@@ -0,0 +1,214 @@
+// Copyright (C) 2015 - IIT Bombay - FOSSEE
+//
+// Author: Harpreet Singh
+// Organization: FOSSEE, IIT Bombay
+// Email: harpreet.mertia@gmail.com
+// This file must be used under the terms of the CeCILL.
+// This source file is licensed as described in the file COPYING, which
+// you should have received as part of this distribution.  The terms
+// are also available at
+// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
+
+
+function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin)
+  // Solves a linear quadratic problem.
+  //
+  //   Calling Sequence
+  //   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( ... )
+  //   
+  //   Parameters
+  //   H : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
+  //   f : a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem
+  //   A : a m x n matrix of doubles, represents the linear coefficients in the inequality constraints
+  //   b : a column vector of doubles, represents the linear coefficients in the inequality constraints
+  //   Aeq : a meq x n 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 n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.
+  //   UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.
+  //   xopt : a nx1 matrix of doubles, the computed solution of the optimization problem.
+  //   fopt : a 1x1 matrix of doubles, 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];
+  //      //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;
+  //    
+  // 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] = qpipopt_mat(H,f,A,b,[],[],lb,ub)
+  //
+  // Authors
+  // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
+    
+    
+//To check the number of input and output argument
+   [lhs , rhs] = argn();
+	
+//To check the number of argument given by user
+   if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 8 ) then
+    errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8]"), "qpipopt", rhs);
+    error(errmsg)
+   end
+   
+   H = varargin(1);
+   f = varargin(2);
+   nbVar = size(H,1);
+
+   
+   if ( rhs<2 ) then
+      A = []
+      b = []
+   else
+      A = varargin(3);
+      b = varargin(4);
+  end
+      
+   if ( rhs<4 ) then
+      Aeq = []
+      beq = []
+   else
+      Aeq = varargin(5);
+      beq = varargin(6);
+  end
+  
+  if ( rhs<6 ) then
+      LB = repmat(-%inf,nbVar,1);
+      UB = repmat(%inf,nbVar,1);
+   else
+      LB = varargin(7);
+      UB = varargin(8);
+  end
+  
+   nbConInEq = size(A,1);
+   nbConEq = size(Aeq,1);
+
+   //Checking the H matrix which needs to be a symmetric matrix
+   if ( H~=H') then
+      errmsg = msprintf(gettext("%s: H is not a symmetric matrix"), "qpipopt_mat");
+      error(errmsg);
+   end
+
+   //Check the size of H which should equal to the number of variable
+   if ( size(H) ~= [nbVar nbVar]) then
+      errmsg = msprintf(gettext("%s: The Size of H is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+   
+   //Check the size of f which should equal to the number of variable
+   if ( size(f,1) ~= [nbVar]) then
+      errmsg = msprintf(gettext("%s: The Size of f is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+   
+   
+   //Check the size of inequality constraint which should be equal to the number of variables
+   if ( size(A,2) ~= nbVar & size(A,2) ~= 0) then
+      errmsg = msprintf(gettext("%s: The size of inequality constraints is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+   //Check the size of equality constraint which should be equal to the number of variables
+   if ( size(Aeq,2) ~= nbVar & size(Aeq,2) ~= 0 ) then
+      errmsg = msprintf(gettext("%s: The size of equality constraints is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+
+   //Check the size of Lower Bound which should be equal to the number of variables
+   if ( size(LB,1) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+//Check the size of Upper Bound which should equal to the number of variables
+   if ( size(UB,1) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+//Check the size of constraints of Lower Bound which should equal to the number of constraints
+   if ( size(b,1) ~= nbConInEq & size(b,1) ~= 0) then
+      errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraints is not equal to the number of constraints"), "qpipopt");
+      error(errmsg);
+   end
+
+//Check the size of constraints of Upper Bound which should equal to the number of constraints
+   if ( size(beq,1) ~= nbConEq & size(beq,1) ~= 0) then
+      errmsg = msprintf(gettext("%s: The Upper Bound of equality constraints is not equal to the number of constraints"), "qp_ipopt");
+      error(errmsg);
+   end
+   
+   //Converting it into ipopt format
+   f = f';
+   LB = LB';
+   UB = UB';
+   conMatrix = [Aeq;A];
+   nbCon = size(conMatrix,1);
+   conLB = [beq; repmat(-%inf,nbConInEq,1)]';
+   conUB = [beq;b]' ; 
+   [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB);
+   
+   xopt = xopt';
+   exitflag = status;
+   output = struct("Iterations"      , []);
+   output.Iterations = iter;
+   lambda = struct("lower"           , [], ..
+                   "upper"           , [], ..
+                   "ineqlin"         , [], ..
+                   "eqlin"           , []);
+   
+   lambda.lower = Zl;
+   lambda.upper = Zu;
+   lambda.eqlin = lmbda(1:nbConEq);
+   lambda.ineqlin = lmbda(nbConEq+1:nbCon);
+    
+
+endfunction
diff --git a/macros/qpipopt_mat.sci~ b/macros/qpipopt_mat.sci~
new file mode 100644
index 0000000..4c72216
--- /dev/null
+++ b/macros/qpipopt_mat.sci~
@@ -0,0 +1,214 @@
+// Copyright (C) 2015 - IIT Bombay - FOSSEE
+//
+// Author: Harpreet Singh
+// Organization: FOSSEE, IIT Bombay
+// Email: harpreet.mertia@gmail.com
+// This file must be used under the terms of the CeCILL.
+// This source file is licensed as described in the file COPYING, which
+// you should have received as part of this distribution.  The terms
+// are also available at
+// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
+
+
+function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin)
+  // Solves a linear quadratic problem.
+  //
+  //   Calling Sequence
+  //   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( ... )
+  //   
+  //   Parameters
+  //   H : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
+  //   f : a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem
+  //   A : a m x n matrix of doubles, represents the linear coefficients in the inequality constraints
+  //   b : a column vector of doubles, represents the linear coefficients in the inequality constraints
+  //   Aeq : a meq x n 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 n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.
+  //   UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.
+  //   xopt : a nx1 matrix of doubles, the computed solution of the optimization problem.
+  //   fopt : a 1x1 matrix of doubles, 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];
+  //      //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;
+  //    
+  // 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] = qpipopt_mat(H,f,A,b,[],[],lb,ub)
+  //
+  // Authors
+  // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
+    
+    
+//To check the number of input and output argument
+   [lhs , rhs] = argn();
+	
+//To check the number of argument given by user
+   if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 8 ) then
+    errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8]"), "qpipopt", rhs);
+    error(errmsg)
+   end
+   
+   H = varargin(1);
+   f = varargin(2);
+   nbVar = size(H,1);
+
+   
+   if ( rhs<2 ) then
+      A = []
+      b = []
+   else
+      A = varargin(3);
+      b = varargin(4);
+  end
+      
+   if ( rhs<4 ) then
+      Aeq = []
+      beq = []
+   else
+      Aeq = varargin(5);
+      beq = varargin(6);
+  end
+  
+  if ( rhs<6 ) then
+      LB = repmat(-%inf,nbVar,1);
+      UB = repmat(%inf,nbVar,1);
+   else
+      LB = varargin(7);
+      UB = varargin(8);
+  end
+  
+   nbConInEq = size(A,1);
+   nbConEq = size(Aeq,1);
+
+   //Checking the H matrix which needs to be a symmetric matrix
+   if ( H~=H') then
+      errmsg = msprintf(gettext("%s: H is not a symmetric matrix"), "qpipopt_mat");
+      error(errmsg);
+   end
+
+   //Check the size of H which should equal to the number of variable
+   if ( size(H) ~= [nbVar nbVar]) then
+      errmsg = msprintf(gettext("%s: The Size of H is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+   
+   //Check the size of f which should equal to the number of variable
+   if ( size(f,1) ~= [nbVar]) then
+      errmsg = msprintf(gettext("%s: The Size of f is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+   
+   
+   //Check the size of inequality constraint which should be equal to the number of variables
+   if ( size(A,2) ~= nbVar & size(A,2) ~= 0) then
+      errmsg = msprintf(gettext("%s: The size of inequality constraints is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+   //Check the size of equality constraint which should be equal to the number of variables
+   if ( size(Aeq,2) ~= nbVar & size(Aeq,2) ~= 0 ) then
+      errmsg = msprintf(gettext("%s: The size of equality constraints is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+
+   //Check the size of Lower Bound which should be equal to the number of variables
+   if ( size(LB,1) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+//Check the size of Upper Bound which should equal to the number of variables
+   if ( size(UB,1) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+
+//Check the size of constraints of Lower Bound which should equal to the number of constraints
+   if ( size(b,1) ~= nbConInEq & size(b,1) ~= 0) then
+      errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraints is not equal to the number of constraints"), "qpipopt");
+      error(errmsg);
+   end
+
+//Check the size of constraints of Upper Bound which should equal to the number of constraints
+   if ( size(beq,1) ~= nbConEq & size(beq,1) ~= 0) then
+      errmsg = msprintf(gettext("%s: The Upper Bound of equality constraints is not equal to the number of constraints"), "qp_ipopt");
+      error(errmsg);
+   end
+   
+   //Converting it into ipopt format
+   f = f';
+   LB = LB';
+   UB = UB';
+   conMatrix = [Aeq;A];
+   nbCon = size(conMatrix,1);
+   conLB = [beq; repmat(-%inf,nbConInEq,1)]';
+   conUB = [beq;b]' ; 
+   [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB);
+   
+   xopt = xopt';
+   exitflag = status;
+   output = struct("Iterations"      , []);
+   output.Iterations = iter;
+   lambda = struct("lower"           , [], ..
+                   "upper"           , [], ..
+                   "ineqlin"         , [], ..
+                   "eqlin"           , []);
+   
+   lambda.lower = Zl;
+   lambda.upper = Zu;
+   lambda.eqlin = lmbda(1:nbConEq);
+   lambda.ineqlin = lmbda(nbConEq+1:nbCon);
+    
+
+endfunction
diff --git a/macros/symphony_mat.bin b/macros/symphony_mat.bin
index 3b72644..600bd9a 100644
--- a/macros/symphony_mat.bin
+++ b/macros/symphony_mat.bin
diff --git a/macros/symphony_mat.sci b/macros/symphony_mat.sci
index 068e9cf..b30d84d 100644
--- a/macros/symphony_mat.sci
+++ b/macros/symphony_mat.sci
@@ -153,7 +153,7 @@ function [xopt,fopt,status,iter] = symphony_mat (varargin)
    [lhs , rhs] = argn();
 	
 //To check the number of argument given by user
-   if ( rhs < 4 | rhs = 5 | rhs = 7 | rhs > 9 ) then
+   if ( rhs < 4 | rhs == 5 | rhs == 7 | rhs > 9 ) then
     errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set [4 6 8 9]"), "Symphony", rhs);
     error(errmsg)
    end
diff --git a/sci_gateway/cpp/QuadNLP.hpp b/sci_gateway/cpp/QuadNLP.hpp
index eff92da..6f01241 100644
--- a/sci_gateway/cpp/QuadNLP.hpp
+++ b/sci_gateway/cpp/QuadNLP.hpp
@@ -23,48 +23,48 @@ using namespace Ipopt;
 class QuadNLP : public TNLP
 {
 	private:
-		Index numVars_;		// Number of variables.
+		Index numVars_;			// Number of variables.
 	
-		Index numConstr_; 	// Number of constraints.
+		Index numConstr_; 		// Number of constraints.
 
-		Number *qMatrix_;	//qMatrix_ is a pointer to matrix of size numVars X numVars_ 
-					// with coefficents of quadratic terms in objective function.
+		const Number *qMatrix_ = NULL;	//qMatrix_ is a pointer to matrix of size numVars X numVars_ 
+						// with coefficents of quadratic terms in objective function.
 
-		Number *lMatrix_;	//lMatrix_ is a pointer to matrix of size 1*numVars_
-					// with coefficents of linear terms in objective function.	
+		const Number *lMatrix_ = NULL;//lMatrix_ is a pointer to matrix of size 1*numVars_
+						// with coefficents of linear terms in objective function.	
 	
-		Number *conMatrix_;	//conMatrix_ is a pointer to matrix of size numConstr X numVars
-					// with coefficients of terms in a each objective in each row.
+		const Number *conMatrix_ = NULL;//conMatrix_ is a pointer to matrix of size numConstr X numVars
+						// with coefficients of terms in a each objective in each row.
 
-		Number *conUB_;		//conUB_ is a pointer to a matrix of size of 1*numConstr_
-					// with upper bounds of all constraints.
+		const Number *conUB_= NULL;	//conUB_ is a pointer to a matrix of size of 1*numConstr_
+						// with upper bounds of all constraints.
 
-		Number *conLB_;		//conLB_ is a pointer to a matrix of size of 1*numConstr_ 
-					// with lower bounds of all constraints.
+		const Number *conLB_ = NULL;	//conLB_ is a pointer to a matrix of size of 1*numConstr_ 
+						// with lower bounds of all constraints.
 
-		Number *varUB_;		//varUB_ is a pointer to a matrix of size of 1*numVar_ 
-					// with upper bounds of all variables.
+		const Number *varUB_= NULL;	//varUB_ is a pointer to a matrix of size of 1*numVar_ 
+						// with upper bounds of all variables.
 
-		Number *varLB_;		//varLB_ is a pointer to a matrix of size of 1*numVar_
-					// with lower bounds of all variables.
-
-		Number *finalX_;	//finalX_ is a pointer to a matrix of size of 1*numVar_
-					// with final value for the primal variables.
+		const Number *varLB_= NULL;	//varLB_ is a pointer to a matrix of size of 1*numVar_
+						// with lower bounds of all variables.
+	
+		Number *finalX_= NULL;		//finalX_ is a pointer to a matrix of size of 1*numVar_
+						// with final value for the primal variables.
 
-		Number *finalZl_;	//finalZl_ is a pointer to a matrix of size of 1*numVar_
-					// with final values for the lower bound multipliers
+		Number *finalZl_= NULL;		//finalZl_ is a pointer to a matrix of size of 1*numVar_
+						// with final values for the lower bound multipliers
 
-		Number *finalZu_;	//finalZu_ is a pointer to a matrix of size of 1*numVar_
-					// with final values for the upper bound multipliers
+		Number *finalZu_= NULL;		//finalZu_ is a pointer to a matrix of size of 1*numVar_
+						// with final values for the upper bound multipliers
 
-		Number *finalLambda_; 	//finalLambda_ is a pointer to a matrix of size of 1*numConstr_
-					// with final values for the upper bound multipliers
+		Number *finalLambda_= NULL;	//finalLambda_ is a pointer to a matrix of size of 1*numConstr_
+						// with final values for the upper bound multipliers
 
-		Number finalObjVal_;	//finalObjVal_ is a scalar with the final value of the objective.
+		Number finalObjVal_;		//finalObjVal_ is a scalar with the final value of the objective.
 
-		int iter_;		//Number of iteration.
+		int iter_;			//Number of iteration.
 
-		int status_;		//Solver return status
+		int status_;			//Solver return status
  
 		QuadNLP(const QuadNLP&);
 		QuadNLP& operator=(const QuadNLP&);
diff --git a/sci_gateway/cpp/QuadNLP.hpp~ b/sci_gateway/cpp/QuadNLP.hpp~
new file mode 100644
index 0000000..f47ab4d
--- /dev/null
+++ b/sci_gateway/cpp/QuadNLP.hpp~
@@ -0,0 +1,131 @@
+/*
+ * Quadratic Programming Toolbox for Scilab using IPOPT library
+ * Authors :
+	Sai Kiran
+	Keyur Joshi
+	Iswarya
+
+
+ * Optimizing (minimizing) the quadratic objective function having any number of variables and linear constraints.
+ *
+*/
+
+#ifndef __QuadNLP_HPP__
+#define __QuadNLP_HPP__
+
+#include "IpTNLP.hpp"
+extern "C"{
+#include <sciprint.h>
+
+}
+using namespace Ipopt;
+
+class QuadNLP : public TNLP
+{
+	private:
+		Index numVars_;			// Number of variables.
+	
+		Index numConstr_; 		// Number of constraints.
+
+		const Number *qMatrix_ = NULL;	//qMatrix_ is a pointer to matrix of size numVars X numVars_ 
+						// with coefficents of quadratic terms in objective function.
+
+		const Number *lMatrix_ = NULL;//lMatrix_ is a pointer to matrix of size 1*numVars_
+						// with coefficents of linear terms in objective function.	
+	
+		const Number *conMatrix_ = NULL;//conMatrix_ is a pointer to matrix of size numConstr X numVars
+						// with coefficients of terms in a each objective in each row.
+
+		const Number *conUB_= NULL;	//conUB_ is a pointer to a matrix of size of 1*numConstr_
+						// with upper bounds of all constraints.
+
+		const Number *conLB_;		//conLB_ is a pointer to a matrix of size of 1*numConstr_ 
+						// with lower bounds of all constraints.
+
+		const Number *varUB_;		//varUB_ is a pointer to a matrix of size of 1*numVar_ 
+						// with upper bounds of all variables.
+
+		const Number *varLB_;		//varLB_ is a pointer to a matrix of size of 1*numVar_
+						// with lower bounds of all variables.
+	
+		Number *finalX_;		//finalX_ is a pointer to a matrix of size of 1*numVar_
+						// with final value for the primal variables.
+
+		Number *finalZl_;		//finalZl_ is a pointer to a matrix of size of 1*numVar_
+						// with final values for the lower bound multipliers
+
+		Number *finalZu_;		//finalZu_ is a pointer to a matrix of size of 1*numVar_
+						// with final values for the upper bound multipliers
+
+		Number *finalLambda_; 		//finalLambda_ is a pointer to a matrix of size of 1*numConstr_
+						// with final values for the upper bound multipliers
+
+		Number finalObjVal_;		//finalObjVal_ is a scalar with the final value of the objective.
+
+		int iter_;			//Number of iteration.
+
+		int status_;			//Solver return status
+ 
+		QuadNLP(const QuadNLP&);
+		QuadNLP& operator=(const QuadNLP&);
+	public:
+		/*
+		 * Constructor 
+		*/
+		QuadNLP(Index nV, Index nC, Number *qM, Number *lM, Number *cM, Number *cUB, Number *cLB, Number *vUB, Number *vLB):
+			numVars_(nV),numConstr_(nC),qMatrix_(qM),lMatrix_(lM),conMatrix_(cM),conUB_(cUB),conLB_(cLB),varUB_(vUB),varLB_(vLB),finalX_(0), finalZl_(0), finalZu_(0), finalObjVal_(1e20){	}
+
+
+		/* Go to :
+
+	http://www.coin-or.org/Ipopt/documentation/node23.html#SECTION00053130000000000000
+		For details about these below methods.
+		*/
+		virtual ~QuadNLP();
+		virtual bool get_nlp_info(Index& n, Index& m, Index& nnz_jac_g,
+								  Index& nnz_h_lag, IndexStyleEnum& index_style);
+		virtual bool get_bounds_info(Index n, Number* x_l, Number* x_u,
+									 Index m, Number* g_l, Number* g_u);
+		virtual bool get_starting_point(Index n, bool init_x, Number* x,
+										bool init_z, Number* z_L, Number* z_U,
+										Index m, bool init_lambda,
+										Number* lambda);
+		virtual bool eval_f(Index n, const Number* x, bool new_x, Number& obj_value);
+		virtual bool eval_grad_f(Index n, const Number* x, bool new_x, Number* grad_f);
+		virtual bool eval_g(Index n, const Number* x, bool new_x, Index m, Number* g);
+		virtual bool eval_jac_g(Index n, const Number* x, bool new_x,
+								Index m, Index nele_jac, Index* iRow, Index *jCol,
+								Number* values);
+		virtual bool eval_h(Index n, const Number* x, bool new_x,
+							Number obj_factor, Index m, const Number* lambda,
+							bool new_lambda, Index nele_hess, Index* iRow,
+							Index* jCol, Number* values);
+		virtual void finalize_solution(SolverReturn status,
+						   Index n, const Number* x, const Number* z_L, const Number* z_U,
+						   Index m, const Number* g, const Number* lambda, Number obj_value,
+						   const IpoptData* ip_data,
+						   IpoptCalculatedQuantities* ip_cq);
+		
+		const double * getX();		//Returns a pointer to a matrix of size of 1*numVar 
+						// with final value for the primal variables.
+
+		const double * getZu();		//Returns a pointer to a matrix of size of 1*numVars
+						// with final values for the upper bound multipliers
+
+		const double * getZl();		//Returns a pointer to a matrix of size of 1*numVars
+						// with final values for the upper bound multipliers
+
+		const double * getLambda();	//Returns a pointer to a matrix of size of 1*numConstr
+						// with final values for the constraint multipliers
+
+
+		double getObjVal();		//Returns the output of the final value of the objective.
+
+		double iterCount();		//Returns the iteration count
+
+		int returnStatus();		//Returns the status count
+
+		
+};
+
+#endif __QuadNLP_HPP__
diff --git a/sci_gateway/cpp/libFAMOS.so b/sci_gateway/cpp/libFAMOS.so
index f148cca..5e885f4 100755
--- a/sci_gateway/cpp/libFAMOS.so
+++ b/sci_gateway/cpp/libFAMOS.so
diff --git a/sci_gateway/cpp/sci_QuadNLP.cpp b/sci_gateway/cpp/sci_QuadNLP.cpp
index 2c484b7..ddca7cf 100644
--- a/sci_gateway/cpp/sci_QuadNLP.cpp
+++ b/sci_gateway/cpp/sci_QuadNLP.cpp
@@ -56,12 +56,11 @@ bool QuadNLP::get_bounds_info(Index n, Number* x_l, Number* x_u, Index m, Number
 //get value of objective function at vector x
 bool QuadNLP::eval_f(Index n, const Number* x, bool new_x, Number& obj_value){
 	unsigned int i,j;
-	Number temp;
 	obj_value=0;
 
-	for (i=0;i<n;++i){
-		for (j=0;j<n;++j){
-			obj_value+=x[i]*x[j]*qMatrix_[n*i+j];			
+	for (i=0;i<=n;i++){
+		for (j=0;j<=n;j++){
+			obj_value+=0.5*x[i]*x[j]*qMatrix_[n*i+j];		
 			}
 		obj_value+=x[i]*lMatrix_[i];
 		}
@@ -71,24 +70,30 @@ bool QuadNLP::eval_f(Index n, const Number* x, bool new_x, Number& obj_value){
 //get value of gradient of objective function at vector x.
 bool QuadNLP::eval_grad_f(Index n, const Number* x, bool new_x, Number* grad_f){
 	unsigned int i,j;
-	for(i=0;i<n;i++){
+	for(i=0;i<n;i++)
+	{
 		grad_f[i]=lMatrix_[i];
 		for(j=0;j<n;j++)
-			grad_f[i]+=(qMatrix_[n*i+j]+qMatrix_[n*j+i])*x[j];
-		}
-	return true;
+			{
+				grad_f[i]+=(qMatrix_[n*i+j])*x[j];
+			}
 	}
+	return true;
+}
 
 //Get the values of constraints at vector x.
 bool QuadNLP::eval_g(Index n, const Number* x, bool new_x, Index m, Number* g){
 	unsigned int i,j;
-	for(i=0;i<m;i++){
+	for(i=0;i<m;i++)
+	{
 		g[i]=0;
 		for(j=0;j<n;j++)
-			g[i]+=x[j]*conMatrix_[n*i+j];
+		{
+			g[i]+=x[j]*conMatrix_[i+j*m];	
 		}
-	return true;
 	}
+	return true;
+}
 
 // This method sets initial values for required vectors . For now we are assuming 0 to all values. 
 bool QuadNLP::get_starting_point(Index n, bool init_x, Number* x,
@@ -137,7 +142,7 @@ bool QuadNLP::eval_jac_g(Index n, const Number* x, bool new_x,
 		int index=0;
 		for (int var=0;var<m;++var)
 			for (int flag=0;flag<n;++flag)
-				values[index++]=conMatrix_[n*var+flag];
+				values[index++]=conMatrix_[var+flag*m];
 		}
 	return true;
 	}
@@ -166,7 +171,7 @@ bool QuadNLP::eval_h(Index n, const Number* x, bool new_x,
 		Index index=0;
 		for (Index row=0;row < n;++row){
 			for (Index col=0; col <= row; ++col){
-				values[index++]=obj_factor*(qMatrix_[n*row+col]+qMatrix_[n*col+row]);
+				values[index++]=obj_factor*(qMatrix_[n*row+col]);
 				}
 			}
 		}
diff --git a/sci_gateway/cpp/sci_QuadNLP.cpp~ b/sci_gateway/cpp/sci_QuadNLP.cpp~
new file mode 100644
index 0000000..4ff99ce
--- /dev/null
+++ b/sci_gateway/cpp/sci_QuadNLP.cpp~
@@ -0,0 +1,255 @@
+/*
+ * Quadratic Programming Toolbox for Scilab using IPOPT library
+ * Authors :
+	Sai Kiran
+	Keyur Joshi
+	Iswarya
+ */
+
+#include "QuadNLP.hpp"
+#include "IpIpoptData.hpp"
+
+extern "C"{
+#include <api_scilab.h>
+#include <Scierror.h>
+#include <BOOL.h>
+#include <localization.h>
+#include <sciprint.h>
+
+
+double x_static,i, *op_obj_x = NULL,*op_obj_value = NULL;
+
+using namespace Ipopt;
+
+QuadNLP::~QuadNLP()
+		 {
+			free(finalX_);
+			free(finalZl_);
+			free(finalZu_);}
+
+//get NLP info such as number of variables,constraints,no.of elements in jacobian and hessian to allocate memory
+bool QuadNLP::get_nlp_info(Index& n, Index& m, Index& nnz_jac_g, Index& nnz_h_lag, IndexStyleEnum& index_style){
+	n=numVars_; // Number of variables
+	m=numConstr_; // Number of constraints
+	nnz_jac_g = n*m; // No. of elements in Jacobian of constraints 
+	nnz_h_lag = n*(n+1)/2; // No. of elements in lower traingle of Hessian of the Lagrangian.
+	index_style=C_STYLE; // Index style of matrices
+	return true;
+	}
+
+//get variable and constraint bound info
+bool QuadNLP::get_bounds_info(Index n, Number* x_l, Number* x_u, Index m, Number* g_l, Number* g_u){
+	
+	unsigned int i;
+	for(i=0;i<n;i++){
+		x_l[i]=varLB_[i];
+		x_u[i]=varUB_[i];
+		sciprint("VarLU %lf %lf \n",x_l[i],x_u[i]);
+		}
+
+	for(i=0;i<m;i++){
+		g_l[i]=conLB_[i];
+		g_u[i]=conUB_[i];
+		sciprint("conLU %lf %lf \n",g_l[i],g_u[i]);
+		}
+	return true;
+	}
+
+//get value of objective function at vector x
+bool QuadNLP::eval_f(Index n, const Number* x, bool new_x, Number& obj_value){
+	unsigned int i,j;
+	obj_value=0;
+
+	for (i=0;i<=n;i++){
+		for (j=0;j<=n;j++){
+			obj_value+=0.5*x[i]*x[j]*qMatrix_[n*i+j];		
+			}
+		obj_value+=x[i]*lMatrix_[i];
+		}
+	return true;
+	}
+
+//get value of gradient of objective function at vector x.
+bool QuadNLP::eval_grad_f(Index n, const Number* x, bool new_x, Number* grad_f){
+	unsigned int i,j;
+	for(i=0;i<n;i++)
+	{
+		grad_f[i]=lMatrix_[i];
+		for(j=0;j<n;j++)
+			{
+				grad_f[i]+=(qMatrix_[n*i+j])*x[j];
+			}
+	}
+	return true;
+}
+
+//Get the values of constraints at vector x.
+bool QuadNLP::eval_g(Index n, const Number* x, bool new_x, Index m, Number* g){
+	unsigned int i,j;
+	for(i=0;i<m;i++)
+	{
+		g[i]=0;
+		for(j=0;j<n;j++)
+		{
+			g[i]+=x[j]*conMatrix_[i+j*m];	
+		}
+	}
+	return true;
+}
+
+// This method sets initial values for required vectors . For now we are assuming 0 to all values. 
+bool QuadNLP::get_starting_point(Index n, bool init_x, Number* x,
+				 bool init_z, Number* z_L, Number* z_U,
+				 Index m, bool init_lambda,
+				 Number* lambda){
+	if (init_x == true){ //we need to set initial values for vector x
+		for (Index var=0;var<n;++var)
+			x[var]=0.0;//initialize with 0 or we can change.
+		}
+
+	if (init_z == true){ //we need to provide initial values for vector bound multipliers
+		for (Index var=0;var<n;++var){
+			z_L[var]=0.0; //initialize with 0 or we can change.
+			z_U[var]=0.0;//initialize with 0 or we can change.
+			}
+		}
+	
+	if (init_lambda == true){ //we need to provide initial values for lambda values.
+		for (Index var=0;var<m;++var){
+			lambda[var]=0.0; //initialize with 0 or we can change.
+			}
+		}
+
+	return true;
+	}
+/* Return either the sparsity structure of the Jacobian of the constraints, or the values for the Jacobian of the constraints at the point x.
+
+*/ 
+bool QuadNLP::eval_jac_g(Index n, const Number* x, bool new_x,
+			 Index m, Index nele_jac, Index* iRow, Index *jCol,
+			 Number* values){
+	
+	//It asked for structure of jacobian.
+	if (values==NULL){ //Structure of jacobian (full structure)
+		int index=0;
+		for (int var=0;var<m;++var)//no. of constraints
+			for (int flag=0;flag<n;++flag){//no. of variables
+				iRow[index]=var;
+				jCol[index]=flag;
+				index++;
+				}
+		}
+	//It asked for values
+	else { 
+		int index=0;
+		for (int var=0;var<m;++var)
+			for (int flag=0;flag<n;++flag)
+				values[index++]=conMatrix_[var+flag*m];
+		}
+	return true;
+	}
+
+/*
+ * Return either the sparsity structure of the Hessian of the Lagrangian, 
+ * or the values of the Hessian of the Lagrangian  for the given values for
+ * x,lambda,obj_factor.
+*/
+bool QuadNLP::eval_h(Index n, const Number* x, bool new_x,
+		     Number obj_factor, Index m, const Number* lambda,
+		     bool new_lambda, Index nele_hess, Index* iRow,
+		     Index* jCol, Number* values){
+
+	if (values==NULL){
+		Index idx=0;
+		for (Index row = 0; row < n; row++) {
+			for (Index col = 0; col <= row; col++) {
+				iRow[idx] = row;
+				jCol[idx] = col;
+				idx++;
+		  		}
+			}
+		}
+	else {
+		Index index=0;
+		for (Index row=0;row < n;++row){
+			for (Index col=0; col <= row; ++col){
+				values[index++]=obj_factor*(qMatrix_[n*row+col]);
+				}
+			}
+		}
+	return true;
+	}
+
+
+void QuadNLP::finalize_solution(SolverReturn status,
+				Index n, const Number* x, const Number* z_L, const Number* z_U,
+				Index m, const Number* g, const Number* lambda, Number obj_value,
+				const IpoptData* ip_data,
+				IpoptCalculatedQuantities* ip_cq){
+	
+	finalX_ = (double*)malloc(sizeof(double) * numVars_ * 1);
+	for (Index i=0; i<n; i++) 
+	{
+    		 finalX_[i] = x[i];
+	}
+	
+	finalZl_ = (double*)malloc(sizeof(double) * numVars_ * 1);
+	for (Index i=0; i<n; i++) 
+	{
+    		 finalZl_[i] = z_L[i];
+	}
+
+	finalZu_ = (double*)malloc(sizeof(double) * numVars_ * 1);
+	for (Index i=0; i<n; i++) 
+	{
+    		 finalZu_[i] = z_U[i];
+	}
+
+	finalLambda_ = (double*)malloc(sizeof(double) * numConstr_ * 1);
+	for (Index i=0; i<m; i++) 
+	{
+    		 finalLambda_[i] = lambda[i];
+	}
+
+	iter_ = ip_data->iter_count();
+	finalObjVal_ = obj_value;
+	status_ = status;
+	
+   }
+
+	const double * QuadNLP::getX()
+	{	
+		return finalX_;
+	}
+
+	const double * QuadNLP::getZl()
+	{	
+		return finalZl_;
+	}
+
+	const double * QuadNLP::getZu()
+	{	
+		return finalZu_;
+	}
+
+	const double * QuadNLP::getLambda()
+	{	
+		return finalLambda_;
+	}
+
+	double QuadNLP::getObjVal()
+	{	
+		return finalObjVal_;
+	}
+
+	double QuadNLP::iterCount()
+	{	
+		return (double)iter_;
+	}
+
+	int QuadNLP::returnStatus()
+	{	
+		return status_;
+	}
+
+}
diff --git a/sci_gateway/cpp/sci_ipopt.cpp b/sci_gateway/cpp/sci_ipopt.cpp
index a7ea33e..06796a9 100644
--- a/sci_gateway/cpp/sci_ipopt.cpp
+++ b/sci_gateway/cpp/sci_ipopt.cpp
@@ -53,25 +53,216 @@ int sci_solveqp(char *fname)
 	
 	CheckInputArgument(pvApiCtx, 9, 9); // We need total 9 input arguments.
 	CheckOutputArgument(pvApiCtx, 7, 7);
-
+	
+	// Error management variable
+	SciErr sciErr;
+	int retVal=0, *piAddressVarQ = NULL,*piAddressVarP = NULL,*piAddressVarCM = NULL,*piAddressVarCUB = NULL,*piAddressVarCLB = NULL, 		*piAddressVarLB = NULL,*piAddressVarUB = NULL;
 	double *QItems=NULL,*PItems=NULL,*ConItems=NULL,*conUB=NULL,*conLB=NULL,*varUB=NULL,*varLB=NULL,x,f,iter;
-	unsigned int nVars,nCons;
+	static unsigned int nVars = 0,nCons = 0;
+	unsigned int temp1 = 0,temp2 = 0;
+
+
+	////////// Manage the input argument //////////
+	
+	
+	//Number of Variables
+	getIntFromScilab(1,&nVars);
+
+	//Number of Constraints
+	getIntFromScilab(2,&nCons);
+
+	temp1 = nVars;
+	temp2 = nCons;
+
+	//Q matrix from scilab
+	/* get Address of inputs */
+	sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddressVarQ);
+	if (sciErr.iErr)
+	{
+		printError(&sciErr, 0);
+		return 0;
+	}
+
+	/* Check that the first input argument is a real matrix (and not complex) */
+	if ( !isDoubleType(pvApiCtx, piAddressVarQ) ||  isVarComplex(pvApiCtx, piAddressVarQ) )
+	{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 3);
+		return 0;
+	}
+
+	/* get matrix */
+	sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarQ, &temp1, &temp1, &QItems);
+	if (sciErr.iErr)
+	{
+	printError(&sciErr, 0);
+	return 0;
+	}
+	
+	//P matrix from scilab
+	/* get Address of inputs */
+	sciErr = getVarAddressFromPosition(pvApiCtx, 4, &piAddressVarP);
+	if (sciErr.iErr)
+	{
+	printError(&sciErr, 0);
+	return 0;
+	}
+
+	/* Check that the first input argument is a real matrix (and not complex) */
+	if ( !isDoubleType(pvApiCtx, piAddressVarP) ||  isVarComplex(pvApiCtx, piAddressVarP) )
+	{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 4);
+		return 0;
+	}
+	
+	temp1 = 1;
+	temp2 = nVars; 
+	/* get matrix */
+	sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarP, &temp1,&temp2, &PItems);
+	if (sciErr.iErr)
+	{
+		printError(&sciErr, 0);
+		return 0;
+	}
+
+	if (nCons!=0)
+	{
+		//conMatrix matrix from scilab
+		/* get Address of inputs */
+		sciErr = getVarAddressFromPosition(pvApiCtx, 5, &piAddressVarCM);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
+
+		/* Check that the first input argument is a real matrix (and not complex) */
+		if ( !isDoubleType(pvApiCtx, piAddressVarCM) ||  isVarComplex(pvApiCtx, piAddressVarCM) )
+		{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 5);
+		return 0;
+		}
+		temp1 = nCons;
+		temp2 = nVars;
+
+		/* get matrix */
+		sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarCM,&temp1, &temp2, &ConItems);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
+
+
+		//conLB matrix from scilab
+		/* get Address of inputs */
+		sciErr = getVarAddressFromPosition(pvApiCtx, 6, &piAddressVarCLB);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
 
+		/* Check that the first input argument is a real matrix (and not complex) */
+		if ( !isDoubleType(pvApiCtx, piAddressVarCLB) ||  isVarComplex(pvApiCtx, piAddressVarCLB) )
+		{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 6);
+		return 0;
+		}
+		temp1 = nCons;
+		temp2 = 1;
 
-	unsigned int arg = 1,temp1,temp2;
+		/* get matrix */
+		sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarCLB,&temp1, &temp2, &conLB);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
+		
+		//conUB matrix from scilab
+		/* get Address of inputs */
+		sciErr = getVarAddressFromPosition(pvApiCtx, 7, &piAddressVarCUB);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
 
-	if ( !getIntFromScilab(arg,&nVars) && arg++ && !getIntFromScilab(arg,&nCons) && arg++ &&
-		!getDoubleMatrixFromScilab(arg,&temp1,&temp2,&QItems) && temp1 == nVars && temp2 == nVars && arg++ &&
-		!getDoubleMatrixFromScilab(arg,&temp1,&temp2,&PItems) && temp2 == nVars && arg++ &&
-		!getDoubleMatrixFromScilab(arg,&temp1,&temp2,&ConItems) && temp1 == nCons &&((nCons !=0 && temp2 == nVars)||(temp2==0)) && arg++ &&
-		!getDoubleMatrixFromScilab(arg,&temp1,&temp2,&conLB)  && temp2 == nCons && arg++ &&
-		!getDoubleMatrixFromScilab(arg,&temp1,&temp2,&conUB)  && temp2 == nCons && arg++ &&
-		!getDoubleMatrixFromScilab(arg,&temp1,&temp2,&varLB) && temp2 == nVars && arg++ && 
-		!getDoubleMatrixFromScilab(arg,&temp1,&temp2,&varUB) && temp2 == nVars){
+		/* Check that the first input argument is a real matrix (and not complex) */
+		if ( !isDoubleType(pvApiCtx, piAddressVarCUB) ||  isVarComplex(pvApiCtx, piAddressVarCUB) )
+		{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 7);
+		return 0;
+		}
 
+		temp1 = nCons;
+		temp2 = 1;
 
+		/* get matrix */
+		sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarCUB,&temp1, &temp2, &conUB);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
+		
+	}
+
+	//varLB matrix from scilab
+	/* get Address of inputs */
+	sciErr = getVarAddressFromPosition(pvApiCtx, 8, &piAddressVarLB);
+	if (sciErr.iErr)
+	{
+	printError(&sciErr, 0);
+	return 0;
+	}
+
+	/* Check that the first input argument is a real matrix (and not complex) */
+	if ( !isDoubleType(pvApiCtx, piAddressVarLB) ||  isVarComplex(pvApiCtx, piAddressVarLB) )
+	{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 8);
+		return 0;
+	}
+	temp1 = 1;
+	temp2 = nVars;
+
+	/* get matrix */
+	sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarLB, &temp1,&temp2, &varLB);
+	if (sciErr.iErr)
+	{
+		printError(&sciErr, 0);
+		return 0;
+	}
+
+	//varUB matrix from scilab
+	/* get Address of inputs */
+	sciErr = getVarAddressFromPosition(pvApiCtx, 9, &piAddressVarUB);
+	if (sciErr.iErr)
+	{
+		printError(&sciErr, 0);
+		return 0;
+	}
+	/* Check that the first input argument is a real matrix (and not complex) */
+	if ( !isDoubleType(pvApiCtx, piAddressVarUB) ||  isVarComplex(pvApiCtx, piAddressVarUB) )
+	{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 9);
+		return 0;
+	}
+
+	temp1 = 1;
+	temp2 = nVars;
+
+	/* get matrix */
+	sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarUB, &temp1,&temp2, &varUB);
+	if (sciErr.iErr)
+	{
+		printError(&sciErr, 0);
+		return 0;
+	}
+	
 
 		using namespace Ipopt;
+
 		SmartPtr<QuadNLP> Prob = new QuadNLP(nVars,nCons,QItems,PItems,ConItems,conUB,conLB,varUB,varLB);
 		SmartPtr<IpoptApplication> app = IpoptApplicationFactory();
   		app->RethrowNonIpoptException(true);
@@ -108,7 +299,6 @@ int sci_solveqp(char *fname)
 		double *Lambda = Prob->getLambda();
 		double iteration = Prob->iterCount();
 		int stats = Prob->returnStatus();
-		SciErr sciErr;
 		sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 1, nVars, fX);
 		if (sciErr.iErr)
 		{
@@ -171,14 +361,6 @@ int sci_solveqp(char *fname)
   		// will be decremented and the objects will automatically
   		// be deleted.
 	
-
-		}
-	else {
-
-		sciprint("\nError:: check argument %d\n",arg);
-		return0toScilab();
-		return 1;
-		}
 		
 	return 0;
 	}
diff --git a/sci_gateway/cpp/sci_ipopt.cpp~ b/sci_gateway/cpp/sci_ipopt.cpp~
new file mode 100644
index 0000000..12cbf81
--- /dev/null
+++ b/sci_gateway/cpp/sci_ipopt.cpp~
@@ -0,0 +1,400 @@
+/*
+ * Quadratic Programming Toolbox for Scilab using IPOPT library
+ * Authors :
+	Sai Kiran
+	Keyur Joshi
+	Iswarya
+ */
+
+
+#include "sci_iofunc.hpp"
+#include "IpIpoptApplication.hpp"
+#include "QuadNLP.hpp"
+
+extern "C"{
+#include <api_scilab.h>
+#include <Scierror.h>
+#include <BOOL.h>
+#include <localization.h>
+#include <sciprint.h>
+
+int j;
+double *op_x, *op_obj,*p;
+
+bool readSparse(int arg,int *iRows,int *iCols,int *iNbItem,int** piNbItemRow, int** piColPos, double** pdblReal){
+	SciErr sciErr;
+	int* piAddr = NULL;
+	int iType   = 0;
+	int iRet    = 0;
+	sciErr = getVarAddressFromPosition(pvApiCtx, arg, &piAddr);
+	if(sciErr.iErr)	{
+		printError(&sciErr, 0);
+		return false;
+		}
+	sciprint("\ndone\n");
+	if(isSparseType(pvApiCtx, piAddr)){
+		sciprint("done\n");
+		sciErr =getSparseMatrix(pvApiCtx, piAddr, iRows, iCols, iNbItem, piNbItemRow, piColPos, pdblReal);
+		if(sciErr.iErr)	{
+			printError(&sciErr, 0);
+			return false;
+			}
+		}
+
+	else {
+		sciprint("\nSparse matrix required\n");
+		return false;
+		}
+	return true;
+	}
+
+int sci_solveqp(char *fname)
+{
+	
+	CheckInputArgument(pvApiCtx, 9, 9); // We need total 9 input arguments.
+	CheckOutputArgument(pvApiCtx, 7, 7);
+	
+	// Error management variable
+	SciErr sciErr;
+	int retVal=0, *piAddressVarQ = NULL,*piAddressVarP = NULL,*piAddressVarCM = NULL,*piAddressVarCUB = NULL,*piAddressVarCLB = NULL, 		*piAddressVarLB = NULL,*piAddressVarUB = NULL;
+	double *QItems=NULL,*PItems=NULL,*ConItems=NULL,*conUB=NULL,*conLB=NULL,*varUB=NULL,*varLB=NULL,x,f,iter;
+	static unsigned int nVars = 0,nCons = 0;
+	unsigned int temp1 = 0,temp2 = 0;
+
+
+	////////// Manage the input argument //////////
+	
+	
+	//Number of Variables
+	getIntFromScilab(1,&nVars);
+
+	//Number of Constraints
+	getIntFromScilab(2,&nCons);
+
+	temp1 = nVars;
+	temp2 = nCons;
+
+	//Q matrix from scilab
+	/* get Address of inputs */
+	sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddressVarQ);
+	if (sciErr.iErr)
+	{
+		printError(&sciErr, 0);
+		return 0;
+	}
+
+	/* Check that the first input argument is a real matrix (and not complex) */
+	if ( !isDoubleType(pvApiCtx, piAddressVarQ) ||  isVarComplex(pvApiCtx, piAddressVarQ) )
+	{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 3);
+		return 0;
+	}
+
+	/* get matrix */
+	sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarQ, &temp1, &temp1, &QItems);
+	if (sciErr.iErr)
+	{
+	printError(&sciErr, 0);
+	return 0;
+	}
+	
+	
+		for(int i=0;i<temp1;i++)
+		{	
+			for(int j=0;j<temp1;j++)
+			{	
+				sciprint("conMatrix %lf \t",QItems[temp1*i+j]);
+			}
+		sciprint("\n");
+		}
+
+	//P matrix from scilab
+	/* get Address of inputs */
+	sciErr = getVarAddressFromPosition(pvApiCtx, 4, &piAddressVarP);
+	if (sciErr.iErr)
+	{
+	printError(&sciErr, 0);
+	return 0;
+	}
+
+	/* Check that the first input argument is a real matrix (and not complex) */
+	if ( !isDoubleType(pvApiCtx, piAddressVarP) ||  isVarComplex(pvApiCtx, piAddressVarP) )
+	{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 4);
+		return 0;
+	}
+	
+	temp1 = 1;
+	temp2 = nVars; 
+	/* get matrix */
+	sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarP, &temp1,&temp2, &PItems);
+	if (sciErr.iErr)
+	{
+		printError(&sciErr, 0);
+		return 0;
+	}
+
+	if (nCons!=0)
+	{
+		//conMatrix matrix from scilab
+		/* get Address of inputs */
+		sciErr = getVarAddressFromPosition(pvApiCtx, 5, &piAddressVarCM);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
+
+		/* Check that the first input argument is a real matrix (and not complex) */
+		if ( !isDoubleType(pvApiCtx, piAddressVarCM) ||  isVarComplex(pvApiCtx, piAddressVarCM) )
+		{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 5);
+		return 0;
+		}
+		temp1 = nCons;
+		temp2 = nVars;
+
+		/* get matrix */
+		sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarCM,&temp1, &temp2, &ConItems);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
+
+		for(int i=0;i<temp1;i++)
+		{	
+			for(int j=0;j<temp2;j++)
+			{	
+				sciprint("conMatrix %lf \t",ConItems[i+j*temp1]);
+			}
+		sciprint("\n");
+		}
+
+
+		//conLB matrix from scilab
+		/* get Address of inputs */
+		sciErr = getVarAddressFromPosition(pvApiCtx, 6, &piAddressVarCLB);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
+
+		/* Check that the first input argument is a real matrix (and not complex) */
+		if ( !isDoubleType(pvApiCtx, piAddressVarCLB) ||  isVarComplex(pvApiCtx, piAddressVarCLB) )
+		{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 6);
+		return 0;
+		}
+		temp1 = nCons;
+		temp2 = 1;
+
+		/* get matrix */
+		sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarCLB,&temp1, &temp2, &conLB);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
+		
+		//conUB matrix from scilab
+		/* get Address of inputs */
+		sciErr = getVarAddressFromPosition(pvApiCtx, 7, &piAddressVarCUB);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
+
+		/* Check that the first input argument is a real matrix (and not complex) */
+		if ( !isDoubleType(pvApiCtx, piAddressVarCUB) ||  isVarComplex(pvApiCtx, piAddressVarCUB) )
+		{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 7);
+		return 0;
+		}
+
+		temp1 = nCons;
+		temp2 = 1;
+
+		/* get matrix */
+		sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarCUB,&temp1, &temp2, &conUB);
+		if (sciErr.iErr)
+		{
+		printError(&sciErr, 0);
+		return 0;
+		}
+		for(int i=0;i<nCons;i++){
+			sciprint("ConLU %lf %lf \n",conLB[i],conUB[i]);
+		}
+	}
+
+	//varLB matrix from scilab
+	/* get Address of inputs */
+	sciErr = getVarAddressFromPosition(pvApiCtx, 8, &piAddressVarLB);
+	if (sciErr.iErr)
+	{
+	printError(&sciErr, 0);
+	return 0;
+	}
+
+	/* Check that the first input argument is a real matrix (and not complex) */
+	if ( !isDoubleType(pvApiCtx, piAddressVarLB) ||  isVarComplex(pvApiCtx, piAddressVarLB) )
+	{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 8);
+		return 0;
+	}
+	temp1 = 1;
+	temp2 = nVars;
+
+	/* get matrix */
+	sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarLB, &temp1,&temp2, &varLB);
+	if (sciErr.iErr)
+	{
+		printError(&sciErr, 0);
+		return 0;
+	}
+
+	//varUB matrix from scilab
+	/* get Address of inputs */
+	sciErr = getVarAddressFromPosition(pvApiCtx, 9, &piAddressVarUB);
+	if (sciErr.iErr)
+	{
+		printError(&sciErr, 0);
+		return 0;
+	}
+	/* Check that the first input argument is a real matrix (and not complex) */
+	if ( !isDoubleType(pvApiCtx, piAddressVarUB) ||  isVarComplex(pvApiCtx, piAddressVarUB) )
+	{
+		Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, 9);
+		return 0;
+	}
+
+	temp1 = 1;
+	temp2 = nVars;
+
+	/* get matrix */
+	sciErr = getMatrixOfDouble(pvApiCtx, piAddressVarUB, &temp1,&temp2, &varUB);
+	if (sciErr.iErr)
+	{
+		printError(&sciErr, 0);
+		return 0;
+	}
+	
+	for(int i=0;i<nVars;i++){
+			sciprint("VarLU %lf %lf \n",varLB[i],varUB[i]);
+		}
+
+		using namespace Ipopt;
+
+		SmartPtr<QuadNLP> Prob = new QuadNLP(nVars,nCons,QItems,PItems,ConItems,conUB,conLB,varUB,varLB);
+		SmartPtr<IpoptApplication> app = IpoptApplicationFactory();
+  		app->RethrowNonIpoptException(true);
+
+		// Change some options
+		// Note: The following choices are only examples, they might not be
+		//       suitable for your optimization problem.
+		app->Options()->SetNumericValue("tol", 1e-7);
+		app->Options()->SetStringValue("mu_strategy", "adaptive");
+
+		// Indicates whether all equality constraints are linear 
+		app->Options()->SetStringValue("jac_c_constant", "yes");
+		// Indicates whether all inequality constraints are linear 
+		app->Options()->SetStringValue("jac_d_constant", "yes");	
+		// Indicates whether the problem is a quadratic problem 
+		app->Options()->SetStringValue("hessian_constant", "yes");
+	
+		// Initialize the IpoptApplication and process the options
+		ApplicationReturnStatus status;
+	 	status = app->Initialize();
+		if (status != Solve_Succeeded) {
+		  	sciprint("\n*** Error during initialization!\n");
+			return0toScilab();
+	   	 return (int) status;
+	 	 }
+		 // Ask Ipopt to solve the problem
+		
+		 status = app->OptimizeTNLP(Prob);
+
+		double *fX = Prob->getX();
+		double ObjVal = Prob->getObjVal();
+		double *Zl = Prob->getZl();
+		double *Zu = Prob->getZu();
+		double *Lambda = Prob->getLambda();
+		double iteration = Prob->iterCount();
+		int stats = Prob->returnStatus();
+		sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 1, nVars, fX);
+		if (sciErr.iErr)
+		{
+			printError(&sciErr, 0);
+			return 0;
+		}
+
+		sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 2,1,1,&ObjVal);
+		if (sciErr.iErr)
+		{
+			printError(&sciErr, 0);
+			return 0;
+		}
+
+		sciErr = createMatrixOfInteger32(pvApiCtx, nbInputArgument(pvApiCtx) + 3,1,1,&stats);
+		if (sciErr.iErr)
+		{
+			printError(&sciErr, 0);
+			return 0;
+		}
+
+		sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 4,1,1,&iteration);
+		if (sciErr.iErr)
+		{
+			printError(&sciErr, 0);
+			return 0;
+		}
+
+		sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 5, 1, nVars, Zl);
+		if (sciErr.iErr)
+		{
+			printError(&sciErr, 0);
+			return 0;
+		}
+
+		sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 6, 1, nVars, Zu);
+		if (sciErr.iErr)
+		{
+			printError(&sciErr, 0);
+			return 0;
+		}
+		
+		sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 7, 1, nCons, Lambda);
+		if (sciErr.iErr)
+		{
+			printError(&sciErr, 0);
+			return 0;
+		}
+		
+
+		AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1;
+		AssignOutputVariable(pvApiCtx, 2) = nbInputArgument(pvApiCtx) + 2;		
+		AssignOutputVariable(pvApiCtx, 3) = nbInputArgument(pvApiCtx) + 3;
+		AssignOutputVariable(pvApiCtx, 4) = nbInputArgument(pvApiCtx) + 4;
+		AssignOutputVariable(pvApiCtx, 5) = nbInputArgument(pvApiCtx) + 5;
+		AssignOutputVariable(pvApiCtx, 6) = nbInputArgument(pvApiCtx) + 6;
+		AssignOutputVariable(pvApiCtx, 7) = nbInputArgument(pvApiCtx) + 7;	
+
+  		// As the SmartPtrs go out of scope, the reference count
+  		// will be decremented and the objects will automatically
+  		// be deleted.
+	
+		
+	return 0;
+	}
+
+}
+
+/*
+hessian_constan
+jacobian _constant
+
+j_s_d constant : yes
+*/
+
diff --git a/thirdparty/linux/include/coin/ThirdParty/metis.h b/thirdparty/linux/include/coin/ThirdParty/metis.h
deleted file mode 100644
index 9512477..0000000
--- a/thirdparty/linux/include/coin/ThirdParty/metis.h
+++ /dev/null
@@ -1,37 +0,0 @@
-/*
- * Copyright 1997, Regents of the University of Minnesota
- *
- * metis.h
- *
- * This file includes all necessary header files
- *
- * Started 8/27/94
- * George
- *
- * $Id: metis.h,v 1.1 1998/11/27 17:59:21 karypis Exp $
- */
-
-
-#include <stdio.h>
-#ifdef __STDC__
-#include <stdlib.h>
-#else
-#include <malloc.h>
-#endif
-#include <strings.h>
-#include <string.h>
-#include <ctype.h>
-#include <math.h>
-#include <stdarg.h>
-#include <time.h>
-
-#ifdef DMALLOC
-#include <dmalloc.h>
-#endif
-
-#include <defs.h>
-#include <struct.h>
-#include <macros.h>
-#include <rename.h>
-#include <proto.h>
-
diff --git a/thirdparty/linux/lib/x64/libcoinblas.la b/thirdparty/linux/lib/x64/libcoinblas.la
index a6b6688..10b255e 100755
--- a/thirdparty/linux/lib/x64/libcoinblas.la
+++ b/thirdparty/linux/lib/x64/libcoinblas.la
@@ -32,4 +32,4 @@ dlopen=''
 dlpreopen=''
 
 # Directory that this library needs to be installed in:
-libdir='/home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib'
+libdir='/home/harpreet/Downloads/Ipopt-3.12.4/build/lib'
diff --git a/thirdparty/linux/lib/x64/libcoinlapack.la b/thirdparty/linux/lib/x64/libcoinlapack.la
index 84d48ef..8ba91df 100755
--- a/thirdparty/linux/lib/x64/libcoinlapack.la
+++ b/thirdparty/linux/lib/x64/libcoinlapack.la
@@ -14,7 +14,7 @@ library_names='libcoinlapack.so.1.5.4 libcoinlapack.so.1 libcoinlapack.so'
 old_library=''
 
 # Libraries that this one depends upon.
-dependency_libs=' /home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib/libcoinblas.la -L/usr/lib/gcc/x86_64-linux-gnu/4.8 -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../../lib -L/lib/../lib -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../.. -lgfortran -lm -lquadmath'
+dependency_libs=' /home/harpreet/Downloads/Ipopt-3.12.4/build/lib/libcoinblas.la -L/usr/lib/gcc/x86_64-linux-gnu/4.8 -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../../lib -L/lib/../lib -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../.. -lgfortran -lm -lquadmath'
 
 # Version information for libcoinlapack.
 current=6
@@ -32,4 +32,4 @@ dlopen=''
 dlpreopen=''
 
 # Directory that this library needs to be installed in:
-libdir='/home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib'
+libdir='/home/harpreet/Downloads/Ipopt-3.12.4/build/lib'
diff --git a/thirdparty/linux/lib/x64/libcoinlapack.so.1.5.4 b/thirdparty/linux/lib/x64/libcoinlapack.so.1.5.4
index 92261d0..038c68d 100755
--- a/thirdparty/linux/lib/x64/libcoinlapack.so.1.5.4
+++ b/thirdparty/linux/lib/x64/libcoinlapack.so.1.5.4
diff --git a/thirdparty/linux/lib/x64/libcoinmetis.la b/thirdparty/linux/lib/x64/libcoinmetis.la
deleted file mode 100755
index 7b7155f..0000000
--- a/thirdparty/linux/lib/x64/libcoinmetis.la
+++ /dev/null
@@ -1,35 +0,0 @@
-# libcoinmetis.la - a libtool library file
-# Generated by ltmain.sh - GNU libtool 1.5.22 (1.1220.2.365 2005/12/18 22:14:06)
-#
-# Please DO NOT delete this file!
-# It is necessary for linking the library.
-
-# The name that we can dlopen(3).
-dlname='libcoinmetis.so.1'
-
-# Names of this library.
-library_names='libcoinmetis.so.1.3.4 libcoinmetis.so.1 libcoinmetis.so'
-
-# The name of the static archive.
-old_library=''
-
-# Libraries that this one depends upon.
-dependency_libs=' -lm'
-
-# Version information for libcoinmetis.
-current=4
-age=3
-revision=4
-
-# Is this an already installed library?
-installed=yes
-
-# Should we warn about portability when linking against -modules?
-shouldnotlink=no
-
-# Files to dlopen/dlpreopen
-dlopen=''
-dlpreopen=''
-
-# Directory that this library needs to be installed in:
-libdir='/home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib'
diff --git a/thirdparty/linux/lib/x64/libcoinmetis.so b/thirdparty/linux/lib/x64/libcoinmetis.so
deleted file mode 120000
index 10ed913..0000000
--- a/thirdparty/linux/lib/x64/libcoinmetis.so
+++ /dev/null
@@ -1 +0,0 @@
-libcoinmetis.so.1.3.4
\ No newline at end of file
diff --git a/thirdparty/linux/lib/x64/libcoinmetis.so.1 b/thirdparty/linux/lib/x64/libcoinmetis.so.1
deleted file mode 120000
index 10ed913..0000000
--- a/thirdparty/linux/lib/x64/libcoinmetis.so.1
+++ /dev/null
@@ -1 +0,0 @@
-libcoinmetis.so.1.3.4
\ No newline at end of file
diff --git a/thirdparty/linux/lib/x64/libcoinmetis.so.1.2.4 b/thirdparty/linux/lib/x64/libcoinmetis.so.1.2.4
deleted file mode 100755
index 9e56d07..0000000
--- a/thirdparty/linux/lib/x64/libcoinmetis.so.1.2.4
+++ /dev/null
diff --git a/thirdparty/linux/lib/x64/libcoinmetis.so.1.3.4 b/thirdparty/linux/lib/x64/libcoinmetis.so.1.3.4
deleted file mode 100755
index febeb8d..0000000
--- a/thirdparty/linux/lib/x64/libcoinmetis.so.1.3.4
+++ /dev/null
diff --git a/thirdparty/linux/lib/x64/libcoinmumps.la b/thirdparty/linux/lib/x64/libcoinmumps.la
index 1fc02e2..e64fd30 100755
--- a/thirdparty/linux/lib/x64/libcoinmumps.la
+++ b/thirdparty/linux/lib/x64/libcoinmumps.la
@@ -14,7 +14,7 @@ library_names='libcoinmumps.so.1.5.4 libcoinmumps.so.1 libcoinmumps.so'
 old_library=''
 
 # Libraries that this one depends upon.
-dependency_libs=' /home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib/libcoinmetis.la /home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib/libcoinblas.la -L/usr/lib/gcc/x86_64-linux-gnu/4.8 -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../../lib -L/lib/../lib -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../.. -L/lib/x86_64-linux-gnu -L/usr/lib/x86_64-linux-gnu -lgfortran -lm -lquadmath'
+dependency_libs=' /home/harpreet/Downloads/Ipopt-3.12.4/build/lib/libcoinblas.la -L/usr/lib/gcc/x86_64-linux-gnu/4.8 -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../../lib -L/lib/../lib -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/4.8/../../.. -L/lib/x86_64-linux-gnu -L/usr/lib/x86_64-linux-gnu -lgfortran -lm -lquadmath'
 
 # Version information for libcoinmumps.
 current=6
@@ -32,4 +32,4 @@ dlopen=''
 dlpreopen=''
 
 # Directory that this library needs to be installed in:
-libdir='/home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib'
+libdir='/home/harpreet/Downloads/Ipopt-3.12.4/build/lib'
diff --git a/thirdparty/linux/lib/x64/libcoinmumps.so.1.5.4 b/thirdparty/linux/lib/x64/libcoinmumps.so.1.5.4
index 947ab30..6f582d8 100755
--- a/thirdparty/linux/lib/x64/libcoinmumps.so.1.5.4
+++ b/thirdparty/linux/lib/x64/libcoinmumps.so.1.5.4
diff --git a/thirdparty/linux/lib/x64/libipopt.la b/thirdparty/linux/lib/x64/libipopt.la
index 62bbb46..aebec3d 100755
--- a/thirdparty/linux/lib/x64/libipopt.la
+++ b/thirdparty/linux/lib/x64/libipopt.la
@@ -14,7 +14,7 @@ library_names='libipopt.so.1.10.4 libipopt.so.1 libipopt.so'
 old_library=''
 
 # Libraries that this one depends upon.
-dependency_libs=' /home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib/libcoinmumps.la /home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib/libcoinmetis.la /home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib/libcoinlapack.la /home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib/libcoinblas.la -lgfortran -lquadmath -ldl'
+dependency_libs=' /home/harpreet/Downloads/Ipopt-3.12.4/build/lib/libcoinmumps.la /home/harpreet/Downloads/Ipopt-3.12.4/build/lib/libcoinlapack.la /home/harpreet/Downloads/Ipopt-3.12.4/build/lib/libcoinblas.la -lgfortran -lquadmath -ldl'
 
 # Version information for libipopt.
 current=11
@@ -32,4 +32,4 @@ dlopen=''
 dlpreopen=''
 
 # Directory that this library needs to be installed in:
-libdir='/home/harpreet/symphony_work/Ipopt-3.12.4/symbuild/lib'
+libdir='/home/harpreet/Downloads/Ipopt-3.12.4/build/lib'
diff --git a/thirdparty/linux/lib/x64/libipopt.so.1.10.4 b/thirdparty/linux/lib/x64/libipopt.so.1.10.4
index a5418bf..82e25d1 100755
--- a/thirdparty/linux/lib/x64/libipopt.so.1.10.4
+++ b/thirdparty/linux/lib/x64/libipopt.so.1.10.4
diff --git a/thirdparty/linux/lib/x86/libcoinmetis.la b/thirdparty/linux/lib/x86/libcoinmetis.la
deleted file mode 100755
index b799473..0000000
--- a/thirdparty/linux/lib/x86/libcoinmetis.la
+++ /dev/null
@@ -1,35 +0,0 @@
-# libcoinmetis.la - a libtool library file
-# Generated by ltmain.sh - GNU libtool 1.5.22 (1.1220.2.365 2005/12/18 22:14:06)
-#
-# Please DO NOT delete this file!
-# It is necessary for linking the library.
-
-# The name that we can dlopen(3).
-dlname='libcoinmetis.so.1'
-
-# Names of this library.
-library_names='libcoinmetis.so.1.2.4 libcoinmetis.so.1 libcoinmetis.so'
-
-# The name of the static archive.
-old_library=''
-
-# Libraries that this one depends upon.
-dependency_libs=''
-
-# Version information for libcoinmetis.
-current=3
-age=2
-revision=4
-
-# Is this an already installed library?
-installed=yes
-
-# Should we warn about portability when linking against -modules?
-shouldnotlink=no
-
-# Files to dlopen/dlpreopen
-dlopen=''
-dlpreopen=''
-
-# Directory that this library needs to be installed in:
-libdir='/home/tonio/Ipopt-3.11.0/build/lib'
diff --git a/thirdparty/linux/lib/x86/libcoinmetis.so b/thirdparty/linux/lib/x86/libcoinmetis.so
deleted file mode 120000
index 6fc93b9..0000000
--- a/thirdparty/linux/lib/x86/libcoinmetis.so
+++ /dev/null
@@ -1 +0,0 @@
-libcoinmetis.so.1.2.4
\ No newline at end of file
diff --git a/thirdparty/linux/lib/x86/libcoinmetis.so.1 b/thirdparty/linux/lib/x86/libcoinmetis.so.1
deleted file mode 120000
index 6fc93b9..0000000
--- a/thirdparty/linux/lib/x86/libcoinmetis.so.1
+++ /dev/null
@@ -1 +0,0 @@
-libcoinmetis.so.1.2.4
\ No newline at end of file
diff --git a/thirdparty/linux/lib/x86/libcoinmetis.so.1.2.4 b/thirdparty/linux/lib/x86/libcoinmetis.so.1.2.4
deleted file mode 100755
index 98c694a..0000000
--- a/thirdparty/linux/lib/x86/libcoinmetis.so.1.2.4
+++ /dev/null