From 29e8e8bbd43892c7fa146c165fdf128f786d6a7b Mon Sep 17 00:00:00 2001
From: Harpreet
Date: Mon, 2 Nov 2015 16:20:08 +0530
Subject: README.rst added

---
 macros/README.rst         |  36 +++++++
 macros/README.rst~        |  36 +++++++
 macros/lib                | Bin 480 -> 480 bytes
 macros/names              |   2 +-
 macros/qpipopt.bin        | Bin 29496 -> 33680 bytes
 macros/qpipopt.sci        |  54 ++++++++---
 macros/qpipopt.sci~       | 233 ++++++++++++++++++++++++++++++++++++++++++++
 macros/qpipoptmat.bin     | Bin 31280 -> 38128 bytes
 macros/qpipoptmat.sci     |  74 ++++++++++++--
 macros/qpipoptmat.sci~    | 101 ++++++++++++++-----
 macros/setOptions.bin     | Bin 3164 -> 3040 bytes
 macros/setOptions.sci     |  17 ++--
 macros/setOptions.sci~    |  40 ++++++++
 macros/symphony.bin       | Bin 43716 -> 43868 bytes
 macros/symphony.sci       |  10 +-
 macros/symphony.sci~      | 227 +++++++++++++++++++++++++++++++++++++++++++
 macros/symphony_call.bin  | Bin 3932 -> 4064 bytes
 macros/symphony_call.sci  |   4 +-
 macros/symphony_call.sci~ |  52 ++++++++++
 macros/symphonymat.bin    | Bin 0 -> 45960 bytes
 macros/symphonymat.sci    | 242 ++++++++++++++++++++++++++++++++++++++++++++++
 macros/symphonymat.sci~   | 242 ++++++++++++++++++++++++++++++++++++++++++++++
 22 files changed, 1307 insertions(+), 63 deletions(-)
 create mode 100644 macros/README.rst
 create mode 100644 macros/README.rst~
 create mode 100644 macros/qpipopt.sci~
 create mode 100644 macros/setOptions.sci~
 create mode 100644 macros/symphony.sci~
 create mode 100644 macros/symphony_call.sci~
 create mode 100644 macros/symphonymat.bin
 create mode 100644 macros/symphonymat.sci
 create mode 100644 macros/symphonymat.sci~

(limited to 'macros')

diff --git a/macros/README.rst b/macros/README.rst
new file mode 100644
index 0000000..5a07f63
--- /dev/null
+++ b/macros/README.rst
@@ -0,0 +1,36 @@
+MACROS
+======
+
+These files mainly consist of functions for checking the input and calling the gateway functions
+
+symphony
+--------
+
+It takes the input in symphony style and checks the input. After all the checks call the symphony_call function.
+
+symphonymat
+-----------
+
+It takes the input in symphony style and checks the input. After all the checks call the symphony_call function.
+
+symphony_call
+-------------
+
+It calls the gateway functions to initialize, set options and to solve it. After that it will call the functions to get the solution for the problem.
+
+setOptions
+----------
+
+It will set the options in the symphony.
+
+qpipopt
+-------
+
+It synatize the input and call solveqp in the ipopt style.
+
+qpipopt
+-------
+
+It synatize the input and call solveqp in the quadprog style.
+
+
diff --git a/macros/README.rst~ b/macros/README.rst~
new file mode 100644
index 0000000..5a07f63
--- /dev/null
+++ b/macros/README.rst~
@@ -0,0 +1,36 @@
+MACROS
+======
+
+These files mainly consist of functions for checking the input and calling the gateway functions
+
+symphony
+--------
+
+It takes the input in symphony style and checks the input. After all the checks call the symphony_call function.
+
+symphonymat
+-----------
+
+It takes the input in symphony style and checks the input. After all the checks call the symphony_call function.
+
+symphony_call
+-------------
+
+It calls the gateway functions to initialize, set options and to solve it. After that it will call the functions to get the solution for the problem.
+
+setOptions
+----------
+
+It will set the options in the symphony.
+
+qpipopt
+-------
+
+It synatize the input and call solveqp in the ipopt style.
+
+qpipopt
+-------
+
+It synatize the input and call solveqp in the quadprog style.
+
+
diff --git a/macros/lib b/macros/lib
index 9b505b3..74bf87e 100644
Binary files a/macros/lib and b/macros/lib differ
diff --git a/macros/names b/macros/names
index 40e5934..e068c5a 100644
--- a/macros/names
+++ b/macros/names
@@ -3,4 +3,4 @@ qpipoptmat
 setOptions
 symphony
 symphony_call
-symphony_mat
+symphonymat
diff --git a/macros/qpipopt.bin b/macros/qpipopt.bin
index 0cdc0d9..07db2ad 100644
Binary files a/macros/qpipopt.bin and b/macros/qpipopt.bin differ
diff --git a/macros/qpipopt.sci b/macros/qpipopt.sci
index efcca01..8f3945e 100644
--- a/macros/qpipopt.sci
+++ b/macros/qpipopt.sci
@@ -16,16 +16,13 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //   Calling Sequence
   //   xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB)
   //   xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0)
+  //   xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0,param)
   //   [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
-<<<<<<< HEAD
   //   Q : a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
-=======
-  //   Q : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
->>>>>>> c2679735a3443017e003ca095d0476bae2dd8e40
   //   p : a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem
   //   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.
@@ -33,6 +30,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //   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. 
   //   x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables.
+  //   param : a list containing the the parameters to be set.
   //   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.
@@ -69,7 +67,9 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //      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)
+  //      x0 = repmat(0,nbVar,1);
+  //	  param = list("MaxIter", 300, "CpuTime", 100);
+  //      [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param)
   //    
   // Examples 
   //    //Find the value of x that minimize following function
@@ -98,8 +98,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
    [lhs , rhs] = argn();
 	
 //To check the number of argument given by user
-   if ( rhs < 9 | rhs > 10 ) then
-    errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9 or 10"), "qpipopt", rhs);
+   if ( rhs < 9 | rhs > 11 ) then
+    errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9, 10 or 11"), "qpipopt", rhs);
     error(errmsg)
    end
    
@@ -113,22 +113,53 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
    conMatrix = varargin(7);
    conLB = varargin(8);
    conUB = varargin(9);
+
    
-   if ( rhs<10 ) then
-      x0 = repmat(0,1,nbVar)
+   if ( rhs<10 | size(varargin(10)) ==0 ) then
+      x0 = repmat(0,nbVar,1);
    else
       x0 = varargin(10);
   end
    
+   if ( rhs<11 ) then
+      param = list(); 
+   else
+      param =varargin(11);
+   end
+   
+   if (modulo(size(param),2)) then
+	errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipopt");
+	error(errmsg);
+   end
+
+
+   options = list(..
+      "MaxIter"     , [3000], ...
+      "CpuTime"   , [600] ...
+      );
+
+   for i = 1:(size(param))/2
+       	select param(2*i-1)
+    	case "MaxIter" then
+          		options(2*i) = param(2*i);
+       	case "CpuTime" then
+          		options(2*i) = param(2*i);
+    	else
+    	      errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipopt", param(2*i-1));
+    	      error(errmsg)
+    	end
+   end
+
    //IPOpt wants it in row matrix form
    p = p';
    LB = LB';
    UB = UB';
    conLB = conLB';
    conUB = conUB';
+   x0 = x0';
    
    //Checking the Q matrix which needs to be a symmetric matrix
-   if ( Q~=Q') then
+   if ( ~isequal(Q,Q') ) then
       errmsg = msprintf(gettext("%s: Q is not a symmetric matrix"), "qpipopt");
       error(errmsg);
    end
@@ -182,7 +213,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
       error(errmsg);
    end
     
-   [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0);
+   
+   [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options);
    
    xopt = xopt';
    exitflag = status;
diff --git a/macros/qpipopt.sci~ b/macros/qpipopt.sci~
new file mode 100644
index 0000000..35e604b
--- /dev/null
+++ b/macros/qpipopt.sci~
@@ -0,0 +1,233 @@
+// 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 = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0)
+  //   xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0,param)
+  //   [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 n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem
+  //   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.
+  //   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. 
+  //   x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables.
+  //   param : a list containing the the parameters to be set.
+  //   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;
+  //      x0 = repmat(0,nbVar,1);
+  //	  param = list("MaxIter", 300, "CpuTime", 100);
+  //      [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param)
+  //    
+  // 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.
+  //	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 | rhs > 11 ) then
+    errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9, 10 or 11"), "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);
+   conUB = varargin(9);
+
+   
+   if ( rhs<10 | size(varargin(10)) ==0 ) then
+      x0 = repmat(0,nbVar,1);
+   else
+      x0 = varargin(10);
+  end
+   
+   if ( rhs<11 ) then
+      param = []; 
+   else
+      param =varargin(11);
+   end
+   
+   if (modulo(size(param),2)) then
+	errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipopt");
+	error(errmsg);
+   end
+
+
+   options = list(..
+      "MaxIter"     , [3000], ...
+      "CpuTime"   , [600] ...
+      );
+
+   for i = 1:(size(param))/2
+       
+       	select param(2*i-1)
+    	case "MaxIter" then
+          		options(1) = param(2*i);
+       	case "CpuTime" then
+          		options(3) = param(2*i);
+    	else
+    	      errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipopt", param(2*i-1));
+    	      error(errmsg)
+    	end
+   end
+
+   //IPOpt wants it in row matrix form
+   p = p';
+   LB = LB';
+   UB = UB';
+   conLB = conLB';
+   conUB = conUB';
+   x0 = x0';
+   
+   //Checking the Q matrix which needs to be a symmetric matrix
+   if ( ~isequal(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"), "qpipopt");
+      error(errmsg);
+   end
+    
+   //Check the size of initial of variables which should equal to the number of variables
+   if ( size(x0,2) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The initial guess of variables is not equal to the number of variables"), "qpipopt");
+      error(errmsg);
+   end
+    
+   
+   [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options);
+   
+   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/qpipoptmat.bin b/macros/qpipoptmat.bin
index 68c3988..668402c 100644
Binary files a/macros/qpipoptmat.bin and b/macros/qpipoptmat.bin differ
diff --git a/macros/qpipoptmat.sci b/macros/qpipoptmat.sci
index 2f3e911..6ae20c0 100644
--- a/macros/qpipoptmat.sci
+++ b/macros/qpipoptmat.sci
@@ -14,11 +14,12 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
   // Solves a linear quadratic problem.
   //
   //   Calling Sequence
-  //   xopt = qpipoptmat(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB)
   //   x = qpipoptmat(H,f)
   //   x = qpipoptmat(H,f,A,b)
   //   x = qpipoptmat(H,f,A,b,Aeq,beq)
   //   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub)
+  //   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0)
+  //   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param)
   //   [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... )
   //   
   //   Parameters
@@ -30,6 +31,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
   //   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.
+  //   x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables.
+  //   param : a list containing the the parameters to be set.
   //   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.
@@ -64,9 +67,11 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
   //      b = [-1; 2.5];
   //      lb=[-1000; -10000; 0; -1000; -1000; -1000];
   //      ub=[10000; 100; 1.5; 100; 100; 1000];
+  //      x0 = repmat(0,6,1);
+  //	  param = list("MaxIter", 300, "CpuTime", 100);
   //      //and minimize 0.5*x'*Q*x + p'*x with
   //      f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
-  //      [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub)
+  //      [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param)
   //      clear H f A b Aeq beq lb ub;
   //    
   // Examples 
@@ -93,8 +98,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
    [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);
+   if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 10 ) then
+    errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8 9 10]"), "qpipoptmat", rhs);
     error(errmsg)
    end
    
@@ -126,7 +131,50 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
       LB = varargin(7);
       UB = varargin(8);
   end
-  
+
+
+  if ( rhs<9 | size(varargin(9)) ==0 ) then
+      x0 = repmat(0,nbVar,1)
+  else
+      x0 = varargin(9);
+  end
+
+   if ( rhs<10 ) then
+      param = list();
+   else
+      param =varargin(10);
+   end
+   
+
+   if (modulo(size(param),2)) then
+	errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipoptmat");
+	error(errmsg);
+   end
+
+   if (modulo(size(param),2)) then
+	errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipoptmat");
+	error(errmsg);
+   end
+
+
+   options = list(..
+      "MaxIter"     , [3000], ...
+      "CpuTime"   , [600] ...
+      );
+
+   for i = 1:(size(param))/2
+        
+       	select param(2*i-1)
+    	case "MaxIter" then
+          		options(2*i-1) = param(2*i);
+       	case "CpuTime" then
+          		options(2*i-1) = param(2*i);
+    	else
+    	      errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipoptmat", param(2*i-1));
+    	      error(errmsg)
+    	end
+   end
+
    nbConInEq = size(A,1);
    nbConEq = size(Aeq,1);
 
@@ -168,33 +216,41 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
       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,1) ~= nbVar) then
       errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipoptmat");
       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(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"), "qpipoptmat");
       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(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"), "qpipoptmat");
       error(errmsg);
    end
+
+   //Check the size of initial of variables which should equal to the number of variables
+   if ( size(x0,1) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The initial guess of variables is not equal to the number of variables"), "qpipoptmat");
+      error(errmsg);
+   end
+
    
    //Converting it into ipopt format
    f = f';
    LB = LB';
    UB = UB';
+   x0 = x0';
    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,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB,x0,options);
    
    xopt = xopt';
    exitflag = status;
diff --git a/macros/qpipoptmat.sci~ b/macros/qpipoptmat.sci~
index 4c72216..e29da8f 100644
--- a/macros/qpipoptmat.sci~
+++ b/macros/qpipoptmat.sci~
@@ -10,16 +10,17 @@
 // http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
 
 
-function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin)
+function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (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( ... )
+  //   x = qpipoptmat(H,f)
+  //   x = qpipoptmat(H,f,A,b)
+  //   x = qpipoptmat(H,f,A,b,Aeq,beq)
+  //   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub)
+  //   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0)
+  //   x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param)
+  //   [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... )
   //   
   //   Parameters
   //   H : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
@@ -30,6 +31,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin)
   //   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.
+  //   x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables.
+  //   param : a list containing the the parameters to be set.
   //   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.
@@ -64,9 +67,11 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin)
   //      b = [-1; 2.5];
   //      lb=[-1000; -10000; 0; -1000; -1000; -1000];
   //      ub=[10000; 100; 1.5; 100; 100; 1000];
+  //      x0 = repmat(0,6,1);
+  //	  param = list("MaxIter", 300, "CpuTime", 100);
   //      //and minimize 0.5*x'*Q*x + p'*x with
   //      f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
-  //      [xopt,fopt,exitflag,output,lambda]=qpipopt_mat(H,f,A,b,Aeq,beq,lb,ub)
+  //      [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param)
   //      clear H f A b Aeq beq lb ub;
   //    
   // Examples 
@@ -83,7 +88,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin)
   //	b = [2; 2; 3];
   //	lb = [0; 0];
   //	ub = [%inf; %inf];
-  //	[xopt,fopt,exitflag,output,lambda] = qpipopt_mat(H,f,A,b,[],[],lb,ub)
+  //	[xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub)
   //
   // Authors
   // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
@@ -93,8 +98,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin)
    [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);
+   if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 10 ) then
+    errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8 9 10]"), "qpipoptmat", rhs);
     error(errmsg)
    end
    
@@ -126,75 +131,121 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin)
       LB = varargin(7);
       UB = varargin(8);
   end
-  
+
+
+  if ( rhs<10 | size(varargin(9)) ==0 ) then
+      x0 = repmat(0,nbVar,1)
+  else
+      x0 = varargin(9);
+  end
+
+   if ( rhs<11 ) then
+      param = list();
+   else
+      param =varargin(10);
+   end
+   
+
+   if (modulo(size(param),2)) then
+	errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipoptmat");
+	error(errmsg);
+   end
+
+
+   options = list(..
+      "MaxIter"     , [3000], ...
+      "CpuTime"   , [600] ...
+      );
+
+   for i = 1:(size(param))/2
+        
+       	select param(2*i-1)
+    	case "MaxIter" then
+          		options(2*i-1) = param(2*i);
+       	case "CpuTime" then
+          		options(2*i-1) = param(2*i);
+    	else
+    	      errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipoptmat", param(2*i-1));
+    	      error(errmsg)
+    	end
+   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");
+      errmsg = msprintf(gettext("%s: H is not a symmetric matrix"), "qpipoptmat");
       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");
+      errmsg = msprintf(gettext("%s: The Size of H is not equal to the number of variables"), "qpipoptmat");
       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");
+      errmsg = msprintf(gettext("%s: The Size of f is not equal to the number of variables"), "qpipoptmat");
       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");
+      errmsg = msprintf(gettext("%s: The size of inequality constraints is not equal to the number of variables"), "qpipoptmat");
       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");
+      errmsg = msprintf(gettext("%s: The size of equality constraints is not equal to the number of variables"), "qpipoptmat");
       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");
+      errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipoptmat");
       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,1) ~= nbVar) then
-      errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipopt");
+      errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipoptmat");
       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(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");
+      errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraints is not equal to the number of constraints"), "qpipoptmat");
       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(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");
+      errmsg = msprintf(gettext("%s: The Upper Bound of equality constraints is not equal to the number of constraints"), "qpipoptmat");
       error(errmsg);
    end
+
+   //Check the size of initial of variables which should equal to the number of variables
+   if ( size(x0,1) ~= nbVar) then
+      errmsg = msprintf(gettext("%s: The initial guess of variables is not equal to the number of variables"), "qpipoptmat");
+      error(errmsg);
+   end
+
    
    //Converting it into ipopt format
    f = f';
    LB = LB';
    UB = UB';
+   x0 = x0';
    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,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB,x0,options);
    
    xopt = xopt';
    exitflag = status;
diff --git a/macros/setOptions.bin b/macros/setOptions.bin
index c5a69df..8d23e73 100644
Binary files a/macros/setOptions.bin and b/macros/setOptions.bin differ
diff --git a/macros/setOptions.sci b/macros/setOptions.sci
index 138e577..68aad02 100644
--- a/macros/setOptions.sci
+++ b/macros/setOptions.sci
@@ -12,9 +12,8 @@
 function setOptions(varargin)
 
     options = varargin(1);
-    nbOpt = size(options,2);
+    nbOpt = size(options);
     
-    value = strtod(options)
 
     if (nbOpt~=0) then
         for i = 1:(nbOpt/2)
@@ -22,21 +21,19 @@ function setOptions(varargin)
         //Setting the parameters
           
             //Check if the given parameter is String
-            if (value(2*i) == %nan ) then
-                sym_setStrParam(options(2*i - 1),value(2*i));
+            if (type(options(2*i)) == 10 ) then
+                sym_setStrParam(options(2*i - 1),options(2*i));
           
             //Check if the given parameter is Double
-            elseif(type(value(2*i))==1) then
-                sym_setDblParam(options(2*i - 1),value(2*i));
+            elseif(type(options(2*i))==1) then
+                sym_setDblParam(options(2*i - 1),options(2*i));
              
             //Check if the given parameter is Integer
-            elseif(type(value(2*i))==8)
+            elseif(type(options(2*i))==8)
                 sym_setIntParam(options(2*i - 1),options(2*i)); 
             end
-          
-        end
+         end
     end
     
-        
 endfunction
 
diff --git a/macros/setOptions.sci~ b/macros/setOptions.sci~
new file mode 100644
index 0000000..ef5c36c
--- /dev/null
+++ b/macros/setOptions.sci~
@@ -0,0 +1,40 @@
+// 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 setOptions(varargin)
+
+    options = varargin(1);
+    nbOpt = size(options);
+    
+
+    if (nbOpt~=0) then
+        for i = 1:(nbOpt/2)
+        
+        //Setting the parameters
+          
+            //Check if the given parameter is String
+            if (type(options(2*i)) == 10 ) then
+                sym_setStrParam(options(2*i - 1),options(2*i));
+          
+            //Check if the given parameter is Double
+            elseif(type(options(2*i))==1) then
+                sym_setDblParam(options(2*i - 1),options(2*i));
+             
+            //Check if the given parameter is Integer
+            elseif(type(options(2*i))==8)
+                sym_setIntParam(options(2*i - 1),options(2*i)); 
+            end
+          
+        end
+    end
+    
+endfunction
+
diff --git a/macros/symphony.bin b/macros/symphony.bin
index ae6c958..d2aa822 100644
Binary files a/macros/symphony.bin and b/macros/symphony.bin differ
diff --git a/macros/symphony.sci b/macros/symphony.sci
index f221160..9677720 100644
--- a/macros/symphony.sci
+++ b/macros/symphony.sci
@@ -71,7 +71,8 @@ function [xopt,fopt,status,output] = symphony (varargin)
   //    xopt = [1 1 0 1 7.25 0 0.25 3.5]
   //    fopt = [8495]
   //    // Calling Symphony
-  //    [x,f,iter] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1);
+  //    [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1)
+  //
     //    Examples
     //    // An advanced case where we set some options in symphony
     //    // This problem is taken from 
@@ -145,7 +146,7 @@ function [xopt,fopt,status,output] = symphony (varargin)
     //    conLB=repmat(0,nbCon,1);
     //    // Upper Bound of constraints
     //    conUB=[11927 13727 11551 13056 13460 ]';
-    //    options = ["time_limit" "25"]
+    //    options = list("time_limit", 25);
     //    // The expected solution :
     //    // Output variables
     //    xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. 
@@ -154,7 +155,7 @@ function [xopt,fopt,status,output] = symphony (varargin)
     //    // Optimal value
     //    fopt = [ 24381 ]
     //    // Calling Symphony
-    //    [x,f,iter]= symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options)
+    //    [x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options)
     //
     // Authors
     // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
@@ -185,7 +186,7 @@ function [xopt,fopt,status,output] = symphony (varargin)
    end
    
    if (rhs<11) then
-      options = [];
+      options = list();
    else
       options = varargin(11);
    end
@@ -224,4 +225,3 @@ function [xopt,fopt,status,output] = symphony (varargin)
    [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options);
 
 endfunction
-
diff --git a/macros/symphony.sci~ b/macros/symphony.sci~
new file mode 100644
index 0000000..d5c8e44
--- /dev/null
+++ b/macros/symphony.sci~
@@ -0,0 +1,227 @@
+// 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,status,output] = symphony (varargin)
+  // Solves a  mixed integer linear programming constrained optimization problem.
+  //
+  //   Calling Sequence
+  //   xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB)
+  //   xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense)
+  //   xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options)
+  //   [xopt,fopt,status,output] = symphony( ... )
+  //   
+  //   Parameters
+  //   nbVar : a 1 x 1 matrix of doubles, number of variables
+  //   nbCon : a 1 x 1 matrix of doubles, number of constraints
+  //   objCoeff : a 1 x n matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective 
+  //   isInt : a 1 x n matrix of boolean, where n is number of variables, representing wether a variable is constrained to be an integer 
+  //   LB : a 1 x n matrix of doubles, where n is number of variables, contains lower bounds of the variables. Bound can be negative infinity
+  //   UB : a 1 x n matrix of doubles, where n is number of variables, contains upper bounds of the variables. Bound can be infinity
+  //   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
+  //   objSense : The sense (maximization/minimization) of the objective. Use 1(sym_minimize ) or -1 (sym_maximize) here
+  //   options : a 1xq marix of string, provided to set the paramters in symphony 
+  //   xopt : a 1xn matrix of doubles, the computed solution of the optimization problem
+  //   fopt : a 1x1 matrix of doubles, the function value at x
+  //   status : status flag from symphony
+  //   output : The output data structure contains detailed informations about the optimization process.
+  //   
+  //   Description
+  //   Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
+  //   find the minimum or maximum of f(x) such that 
+  //
+  //   <latex>
+  //    \begin{eqnarray}
+  //    &\mbox{min}_{x}
+  //    & f(x) \\
+  //    & \text{subject to} & conLB \leq C(x) \leq conUB \\
+  //    & & lb \leq x \leq ub \\
+  //    \end{eqnarray}
+  //   </latex>
+  //   
+  //   We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.
+  //
+  //   Examples
+  //    //A basic case : 
+  //    // Objective function
+  //    c = [350*5,330*3,310*4,280*6,500,450,400,100]
+  //    // Lower Bound of variable
+  //    lb = repmat(0,1,8);
+  //    // Upper Bound of variables
+  //    ub = [repmat(1,1,4) repmat(%inf,1,4)];
+  //    // Constraint Matrix
+  //    conMatrix = [5,3,4,6,1,1,1,1;
+  //                 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03;
+  //                 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;]
+  //    // Lower Bound of constrains
+  //    conlb = [ 25; 1.25; 1.25]
+  //    // Upper Bound of constrains
+  //    conub = [ 25; 1.25; 1.25]
+  //    // Row Matrix for telling symphony that the is integer or not
+  //    isInt = [repmat(%t,1,4) repmat(%f,1,4)];
+  //    xopt = [1 1 0 1 7.25 0 0.25 3.5]
+  //    fopt = [8495]
+  //    // Calling Symphony
+  //    [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1)
+  //
+    //    Examples
+    //    // An advanced case where we set some options in symphony
+    //    // This problem is taken from 
+    //    // P.C.Chu and J.E.Beasley 
+    //    // "A genetic algorithm for the multidimensional knapsack problem",
+    //    // Journal of Heuristics, vol. 4, 1998, pp63-86.
+    //    // The problem to be solved is:
+    //    // Max  sum{j=1,...,n} p(j)x(j)
+    //    // st   sum{j=1,...,n} r(i,j)x(j) <= b(i)       i=1,...,m
+    //    //                     x(j)=0 or 1
+    //    // The function to be maximize i.e. P(j)
+    //    p = [   504 803 667 1103 834 585 811 856 690 832 846 813 868 793 ..
+    //            825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 ..
+    //            877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 ..
+    //            957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 ..
+    //            959 668 507 855 986 831 821 825 868 852 832 828 799 686 ..
+    //            510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 ..
+    //            1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]
+    //    //Constraint Matrix
+    //    conMatrix = [ 
+    //                    //Constraint 1
+    //                    42 41 523 215 819 551 69 193 582 375 367 478 162 898 ..
+    //                    550 553 298 577 493 183 260 224 852 394 958 282 402 604 ..
+    //                    164 308 218 61 273 772 191 117 276 877 415 873 902 465 ..
+    //                    320 870 244 781 86 622 665 155 680 101 665 227 597 354 ..
+    //                    597 79 162 998 849 136 112 751 735 884 71 449 266 420 ..
+    //                    797 945 746 46 44 545 882 72 383 714 987 183 731 301 ..
+    //                    718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298;
+    //                    //Constraint 2
+    //                    509 883 229 569 706 639 114 727 491 481 681 948 687 941 ..
+    //                    350 253 573 40 124 384 660 951 739 329 146 593 658 816 ..
+    //                    638 717 779 289 430 851 937 289 159 260 930 248 656 833 ..
+    //                    892 60 278 741 297 967 86 249 354 614 836 290 893 857 ..
+    //                    158 869 206 504 799 758 431 580 780 788 583 641 32 653 ..
+    //                    252 709 129 368 440 314 287 854 460 594 512 239 719 751 ..
+    //                    708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850;
+    //                    //Constraint 3
+    //                    806 361 199 781 596 669 957 358 259 888 319 751 275 177 ..
+    //                    883 749 229 265 282 694 819 77 190 551 140 442 867 283 ..
+    //                    137 359 445 58 440 192 485 744 844 969 50 833 57 877 ..
+    //                    482 732 968 113 486 710 439 747 174 260 877 474 841 422 ..
+    //                    280 684 330 910 791 322 404 403 519 148 948 414 894 147 ..
+    //                    73 297 97 651 380 67 582 973 143 732 624 518 847 113 ..
+    //                    382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ;
+    //                    //Constraint 4
+    //                    404 197 817 1000 44 307 39 659 46 334 448 599 931 776 ..
+    //                    263 980 807 378 278 841 700 210 542 636 388 129 203 110 ..
+    //                    817 502 657 804 662 989 585 645 113 436 610 948 919 115 ..
+    //                    967 13 445 449 740 592 327 167 368 335 179 909 825 614 ..
+    //                    987 350 179 415 821 525 774 283 427 275 659 392 73 896 ..
+    //                    68 982 697 421 246 672 649 731 191 514 983 886 95 846 ..
+    //                    689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322;
+    //                    //Constrain 5
+    //                    475 36 287 577 45 700 803 654 196 844 657 387 518 143 ..
+    //                    515 335 942 701 332 803 265 922 908 139 995 845 487 100 ..
+    //                    447 653 649 738 424 475 425 926 795 47 136 801 904 740 ..
+    //                    768 460 76 660 500 915 897 25 716 557 72 696 653 933 ..
+    //                    420 582 810 861 758 647 237 631 271 91 75 756 409 440 ..
+    //                    483 336 765 637 981 980 202 35 594 689 602 76 767 693 ..
+    //                    893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ;
+    //     ];
+    //    nbCon = size(conMatrix,1)
+    //    nbVar = size(conMatrix,2)
+    //    // Lower Bound of variables
+    //    lb = repmat(0,1,nbVar)
+    //    // Upper Bound of variables
+    //    ub = repmat(1,1,nbVar)
+    //    // Row Matrix for telling symphony that the is integer or not
+    //    isInt = repmat(%t,1,nbVar)
+    //    // Lower Bound of constrains
+    //    conLB=repmat(0,nbCon,1);
+    //    // Upper Bound of constraints
+    //    conUB=[11927 13727 11551 13056 13460 ]';
+    //    options = ["time_limit" "25"]
+    //    // The expected solution :
+    //    // Output variables
+    //    xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. 
+    //            0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 1 0 ..
+    //            0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0]
+    //    // Optimal value
+    //    fopt = [ 24381 ]
+    //    // Calling Symphony
+    //    [x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options)
+    //
+    // Authors
+    // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
+    
+//To check the number of input and output argument
+   [lhs , rhs] = argn();
+	
+//To check the number of argument given by user
+   if ( rhs < 9 | rhs > 11 ) then
+    errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set [9 10 11]"), "Symphony", rhs);
+    error(errmsg)
+   end
+   
+   nbVar = varargin(1);
+   nbCon = varargin(2);
+   objCoef = varargin(3);
+   isInt = varargin(4);
+   LB = varargin(5);
+   UB = varargin(6);
+   conMatrix = varargin(7);
+   conLB = varargin(8);
+   conUB = varargin(9);
+   
+   if ( rhs<10 ) then
+      objSense = 1;
+   else
+      objSense = varargin(10);
+   end
+   
+   if (rhs<11) then
+      options = list();
+   else
+      options = varargin(11);
+   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"), "Symphony");
+      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"), "Symphony");
+      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"), "Symphony");
+      error(errmsg);
+   end
+
+//Check the size of constraints of Lower Bound which should equal to the number of constraints
+   if ( size(conLB,1) ~= nbCon) then
+      errmsg = msprintf(gettext("%s: The Lower Bound of constraints is not equal to the number of constraints"), "Symphony");
+      error(errmsg);
+   end
+
+//Check the size of constraints of Upper Bound which should equal to the number of constraints
+   if ( size(conUB,1) ~= nbCon) then
+      errmsg = msprintf(gettext("%s: The Upper Bound of constraints is not equal to the number of constraints"), "Symphony");
+      error(errmsg);
+   end
+
+   [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options);
+
+endfunction
diff --git a/macros/symphony_call.bin b/macros/symphony_call.bin
index b95e887..5008236 100644
Binary files a/macros/symphony_call.bin and b/macros/symphony_call.bin differ
diff --git a/macros/symphony_call.sci b/macros/symphony_call.sci
index ea5f34f..c8323fc 100644
--- a/macros/symphony_call.sci
+++ b/macros/symphony_call.sci
@@ -16,7 +16,7 @@ function [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,
 
     //Setting Options for the Symphpony
     setOptions(options);
-
+    
    //Choosing to launch basic or advanced version
     if(~issparse(conMatrix)) then
         sym_loadProblemBasic(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix,conLB,conUB);
@@ -26,8 +26,8 @@ function [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,
         sym_loadProblem(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix_advanced,conLB,conUB);
     end
 
-
     op = sym_solve();
+    disp(op);
     
     xopt = [];
     fopt = [];
diff --git a/macros/symphony_call.sci~ b/macros/symphony_call.sci~
new file mode 100644
index 0000000..057ba63
--- /dev/null
+++ b/macros/symphony_call.sci~
@@ -0,0 +1,52 @@
+// 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,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options)
+
+    //Opening Symphony environment 
+    sym_open();
+
+    //Setting Options for the Symphpony
+//    setOptions(options);
+    
+   //Choosing to launch basic or advanced version
+    if(~issparse(conMatrix)) then
+        sym_loadProblemBasic(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix,conLB,conUB);
+    else
+        // Changing to Constraint Matrix into sparse matrix
+        conMatrix_advanced=sparse(conMatrix);
+        sym_loadProblem(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix_advanced,conLB,conUB);
+    end
+
+    op = sym_solve();
+    disp(op);
+    
+    xopt = [];
+    fopt = [];
+    status = [];
+    output = [];
+    
+     if (~op) then
+            xopt = sym_getVarSoln();
+            // Symphony gives a row matrix converting it to column matrix
+            xopt = xopt';
+            
+            fopt = sym_getObjVal();
+    end
+    
+    status = sym_getStatus();
+    
+    output = struct("Iterations"      , []);
+      
+      output.Iterations = sym_getIterCount();
+
+
+endfunction
diff --git a/macros/symphonymat.bin b/macros/symphonymat.bin
new file mode 100644
index 0000000..5089973
Binary files /dev/null and b/macros/symphonymat.bin differ
diff --git a/macros/symphonymat.sci b/macros/symphonymat.sci
new file mode 100644
index 0000000..ef70b7c
--- /dev/null
+++ b/macros/symphonymat.sci
@@ -0,0 +1,242 @@
+// 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,status,iter] = symphonymat (varargin)
+  // Solves a mixed integer linear programming constrained optimization problem in intlinprog format.
+  //
+  //   Calling Sequence
+  //   xopt = symphonymat(f,intcon,A,b)
+  //   xopt = symphonymat(f,intcon,A,b,Aeq,beq)
+  //   xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub)
+  //   xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub,options)
+  //   [xopt,fopt,status,output] = symphonymat( ... )
+  //   
+  //   Parameters
+  //   f : a 1xn matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective 
+  //   intcon : Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable
+  //   A : Linear inequality constraint matrix, specified as a matrix of doubles. A represents the linear coefficients in the constraints A*x ≤ b. A has size M-by-N, where M is the number of constraints and N is number of variables
+  //   b : Linear inequality constraint vector, specified as a vector of doubles. b represents the constant vector in the constraints A*x ≤ b. b has length M, where A is M-by-N
+  //   Aeq : Linear equality constraint matrix, specified as a matrix of doubles. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has size Meq-by-N, where Meq is the number of constraints and N is number of variables
+  //   beq : Linear equality constraint vector, specified as a vector of doubles. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N. 
+  //   lb : Lower bounds, specified as a vector or array of doubles. lb represents the lower bounds elementwise in lb ≤ x ≤ ub.
+  //   ub : Upper bounds, specified as a vector or array of doubles. ub represents the upper bounds elementwise in lb ≤ x ≤ ub.
+  //   options : a list containing the the parameters to be set.
+  //   xopt : a 1xn matrix of doubles, the computed solution of the optimization problem
+  //   fopt : a 1x1 matrix of doubles, the function value at x
+  //   output : The output data structure contains detailed informations about the optimization process.
+  //   
+  //   Description
+  //   Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
+  //   find the minimum or maximum of f(x) such that 
+  //
+  //   <latex>
+  //    \begin{eqnarray}
+  //    &\mbox{min}_{x}
+  //    & f(x) \\
+  //    & \text{subject to} & conLB \leq C(x) \leq conUB \\
+  //    & & lb \leq x \leq ub \\
+  //    \end{eqnarray}
+  //   </latex>
+  //   
+  //   We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.
+  //
+  // Examples
+  //    // Objective function
+  //    c = [350*5,330*3,310*4,280*6,500,450,400,100]
+  //    // Lower Bound of variable
+  //    lb = repmat(0,1,8);
+  //    // Upper Bound of variables
+  //    ub = [repmat(1,1,4) repmat(%inf,1,4)];
+  //    // Constraint Matrix
+  //    Aeq = [5,3,4,6,1,1,1,1;
+  //                 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03;
+  //                 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;]
+  //    beq = [ 25, 1.25, 1.25]
+  //    intcon = [1 2 3 4];
+  //    // Calling Symphony
+  //    [x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub)
+  //
+  // Examples 
+  //    // An advanced case where we set some options in symphony
+  //    // This problem is taken from 
+  //    // P.C.Chu and J.E.Beasley 
+  //    // "A genetic algorithm for the multidimensional knapsack problem",
+  //    // Journal of Heuristics, vol. 4, 1998, pp63-86.
+  //    // The problem to be solved is:
+  //    // Max  sum{j=1,...,n} p(j)x(j)
+  //    // st   sum{j=1,...,n} r(i,j)x(j) <= b(i)       i=1,...,m
+  //    //                     x(j)=0 or 1
+  //    // The function to be maximize i.e. P(j)
+  //    objCoef = -1*[   504 803 667 1103 834 585 811 856 690 832 846 813 868 793 ..
+  //            825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 ..
+  //            877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 ..
+  //            957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 ..
+  //            959 668 507 855 986 831 821 825 868 852 832 828 799 686 ..
+  //            510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 ..
+  //            1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]
+  //    //Constraint Matrix
+  //    conMatrix = [   //Constraint 1
+  //                    42 41 523 215 819 551 69 193 582 375 367 478 162 898 ..
+  //                    550 553 298 577 493 183 260 224 852 394 958 282 402 604 ..
+  //                    164 308 218 61 273 772 191 117 276 877 415 873 902 465 ..
+  //                    320 870 244 781 86 622 665 155 680 101 665 227 597 354 ..
+  //                    597 79 162 998 849 136 112 751 735 884 71 449 266 420 ..
+  //                    797 945 746 46 44 545 882 72 383 714 987 183 731 301 ..
+  //                    718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298;
+  //                    //Constraint 2
+  //                    509 883 229 569 706 639 114 727 491 481 681 948 687 941 ..
+  //                    350 253 573 40 124 384 660 951 739 329 146 593 658 816 ..
+  //                    638 717 779 289 430 851 937 289 159 260 930 248 656 833 ..
+  //                    892 60 278 741 297 967 86 249 354 614 836 290 893 857 ..
+  //                    158 869 206 504 799 758 431 580 780 788 583 641 32 653 ..
+  //                    252 709 129 368 440 314 287 854 460 594 512 239 719 751 ..
+  //                    708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850;
+  //                    //Constraint 3
+  //                    806 361 199 781 596 669 957 358 259 888 319 751 275 177 ..
+  //                    883 749 229 265 282 694 819 77 190 551 140 442 867 283 ..
+  //                    137 359 445 58 440 192 485 744 844 969 50 833 57 877 ..
+  //                    482 732 968 113 486 710 439 747 174 260 877 474 841 422 ..
+  //                    280 684 330 910 791 322 404 403 519 148 948 414 894 147 ..
+  //                    73 297 97 651 380 67 582 973 143 732 624 518 847 113 ..
+  //                    382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ;
+  //                    //Constraint 4
+  //                    404 197 817 1000 44 307 39 659 46 334 448 599 931 776 ..
+  //                    263 980 807 378 278 841 700 210 542 636 388 129 203 110 ..
+  //                    817 502 657 804 662 989 585 645 113 436 610 948 919 115 ..
+  //                    967 13 445 449 740 592 327 167 368 335 179 909 825 614 ..
+  //                    987 350 179 415 821 525 774 283 427 275 659 392 73 896 ..
+  //                    68 982 697 421 246 672 649 731 191 514 983 886 95 846 ..
+  //                    689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322;
+  //                    //Constrain 5
+  //                    475 36 287 577 45 700 803 654 196 844 657 387 518 143 ..
+  //                    515 335 942 701 332 803 265 922 908 139 995 845 487 100 ..
+  //                    447 653 649 738 424 475 425 926 795 47 136 801 904 740 ..
+  //                    768 460 76 660 500 915 897 25 716 557 72 696 653 933 ..
+  //                    420 582 810 861 758 647 237 631 271 91 75 756 409 440 ..
+  //                    483 336 765 637 981 980 202 35 594 689 602 76 767 693 ..
+  //                    893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ;
+  //     ];
+  //    nbVar = size(objCoef,2)
+  //    conUB=[11927 13727 11551 13056 13460 ];
+  //    // Lower Bound of variables
+  //    lb = repmat(0,1,nbVar)
+  //    // Upper Bound of variables
+  //    ub = repmat(1,1,nbVar)
+  //    // Lower Bound of constrains
+  //    intcon = []
+  //    for i = 1:nbVar
+  //        intcon = [intcon i];
+  //    end
+  //    options = list("time_limit", 25);
+  //    // The expected solution :
+  //    // Output variables
+  //    xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 ..
+  //            0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 ..
+  //            0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0]
+  //    // Optimal value
+  //    fopt = [ 24381 ]
+  //    // Calling Symphony
+  //    [x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options);
+  // 
+  // 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 < 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
+   
+   
+   objCoef = varargin(1)
+   intcon = varargin(2)
+   A = varargin(3)
+   b = varargin(4)
+   
+   nbVar = size(objCoef,2);
+   nbCon = size(A,1);
+   
+   if ( rhs<4 ) then
+      Aeq = []
+      beq = []
+   else
+      Aeq = varargin(5);
+      beq = varargin(6);
+      
+      if (size(Aeq,1)~=0) then
+           //Check the size of equality constraint which should equal to the number of inequality constraints
+            if ( size(Aeq,2) ~= nbVar) then
+                errmsg = msprintf(gettext("%s: The size of equality constraint is not equal to the number of variables"), "Symphony");
+                error(errmsg);
+            end
+          
+          //Check the size of upper bound of inequality constraint which should equal to the number of constraints
+            if ( size(beq,2) ~= size(Aeq,1)) then
+                errmsg = msprintf(gettext("%s: The equality constraint upper bound is not equal to the number of equality constraint"), "Symphony");
+                error(errmsg);
+            end
+      end
+      
+   end
+   
+   if ( rhs<6 ) then
+      lb = repmat(-%inf,1,nbVar);
+      ub = repmat(%inf,1,nbVar);
+   else
+      lb = varargin(7);
+      ub = varargin(8);
+   end
+   
+   if (rhs<9) then
+      options = list();
+   else
+      options = varargin(9);
+   end
+   
+
+//Check the size of lower bound of inequality constraint which should equal to the number of constraints
+   if ( size(b,2) ~= size(A,1)) then
+      errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraint is not equal to the number of constraint"), "Symphony");
+      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"), "Symphony");
+      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"), "Symphony");
+      error(errmsg);
+   end
+   
+    //Changing the inputs in symphony's format 
+    conMatrix = [A;Aeq]
+    nbCon = size(conMatrix,1);
+    conLB = [repmat(-%inf,1,size(A,1)), beq]';
+    conUB = [b,beq]' ; 
+    
+    isInt = repmat(%f,1,nbVar);
+    for i=1:size(intcon,2)
+        isInt(intcon(i)) = %t
+    end
+    
+    objSense = 1;
+    
+   [xopt,fopt,status,iter] = symphony_call(nbVar,nbCon,objCoef,isInt,lb,ub,conMatrix,conLB,conUB,objSense,options);
+
+endfunction
diff --git a/macros/symphonymat.sci~ b/macros/symphonymat.sci~
new file mode 100644
index 0000000..455dd67
--- /dev/null
+++ b/macros/symphonymat.sci~
@@ -0,0 +1,242 @@
+// 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,status,iter] = symphonymat (varargin)
+  // Solves a mixed integer linear programming constrained optimization problem in intlinprog format.
+  //
+  //   Calling Sequence
+  //   xopt = symphonymat(f,intcon,A,b)
+  //   xopt = symphonymat(f,intcon,A,b,Aeq,beq)
+  //   xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub)
+  //   xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub,options)
+  //   [xopt,fopt,status,output] = symphonymat( ... )
+  //   
+  //   Parameters
+  //   f : a 1xn matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective 
+  //   intcon : Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable
+  //   A : Linear inequality constraint matrix, specified as a matrix of doubles. A represents the linear coefficients in the constraints A*x ≤ b. A has size M-by-N, where M is the number of constraints and N is number of variables
+  //   b : Linear inequality constraint vector, specified as a vector of doubles. b represents the constant vector in the constraints A*x ≤ b. b has length M, where A is M-by-N
+  //   Aeq : Linear equality constraint matrix, specified as a matrix of doubles. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has size Meq-by-N, where Meq is the number of constraints and N is number of variables
+  //   beq : Linear equality constraint vector, specified as a vector of doubles. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N. 
+  //   lb : Lower bounds, specified as a vector or array of doubles. lb represents the lower bounds elementwise in lb ≤ x ≤ ub.
+  //   ub : Upper bounds, specified as a vector or array of doubles. ub represents the upper bounds elementwise in lb ≤ x ≤ ub.
+  //   options : a list containing the the parameters to be set.
+  //   xopt : a 1xn matrix of doubles, the computed solution of the optimization problem
+  //   fopt : a 1x1 matrix of doubles, the function value at x
+  //   output : The output data structure contains detailed informations about the optimization process.
+  //   
+  //   Description
+  //   Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
+  //   find the minimum or maximum of f(x) such that 
+  //
+  //   <latex>
+  //    \begin{eqnarray}
+  //    &\mbox{min}_{x}
+  //    & f(x) \\
+  //    & \text{subject to} & conLB \leq C(x) \leq conUB \\
+  //    & & lb \leq x \leq ub \\
+  //    \end{eqnarray}
+  //   </latex>
+  //   
+  //   We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.
+  //
+  // Examples
+  //    // Objective function
+  //    c = [350*5,330*3,310*4,280*6,500,450,400,100]
+  //    // Lower Bound of variable
+  //    lb = repmat(0,1,8);
+  //    // Upper Bound of variables
+  //    ub = [repmat(1,1,4) repmat(%inf,1,4)];
+  //    // Constraint Matrix
+  //    Aeq = [5,3,4,6,1,1,1,1;
+  //                 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03;
+  //                 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;]
+  //    beq = [ 25, 1.25, 1.25]
+  //    intcon = [1 2 3 4];
+  //    // Calling Symphony
+  //    [x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub)
+  //
+  // Examples 
+  //    // An advanced case where we set some options in symphony
+  //    // This problem is taken from 
+  //    // P.C.Chu and J.E.Beasley 
+  //    // "A genetic algorithm for the multidimensional knapsack problem",
+  //    // Journal of Heuristics, vol. 4, 1998, pp63-86.
+  //    // The problem to be solved is:
+  //    // Max  sum{j=1,...,n} p(j)x(j)
+  //    // st   sum{j=1,...,n} r(i,j)x(j) <= b(i)       i=1,...,m
+  //    //                     x(j)=0 or 1
+  //    // The function to be maximize i.e. P(j)
+  //    objCoef = -1*[   504 803 667 1103 834 585 811 856 690 832 846 813 868 793 ..
+  //            825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 ..
+  //            877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 ..
+  //            957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 ..
+  //            959 668 507 855 986 831 821 825 868 852 832 828 799 686 ..
+  //            510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 ..
+  //            1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]
+  //    //Constraint Matrix
+  //    conMatrix = [   //Constraint 1
+  //                    42 41 523 215 819 551 69 193 582 375 367 478 162 898 ..
+  //                    550 553 298 577 493 183 260 224 852 394 958 282 402 604 ..
+  //                    164 308 218 61 273 772 191 117 276 877 415 873 902 465 ..
+  //                    320 870 244 781 86 622 665 155 680 101 665 227 597 354 ..
+  //                    597 79 162 998 849 136 112 751 735 884 71 449 266 420 ..
+  //                    797 945 746 46 44 545 882 72 383 714 987 183 731 301 ..
+  //                    718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298;
+  //                    //Constraint 2
+  //                    509 883 229 569 706 639 114 727 491 481 681 948 687 941 ..
+  //                    350 253 573 40 124 384 660 951 739 329 146 593 658 816 ..
+  //                    638 717 779 289 430 851 937 289 159 260 930 248 656 833 ..
+  //                    892 60 278 741 297 967 86 249 354 614 836 290 893 857 ..
+  //                    158 869 206 504 799 758 431 580 780 788 583 641 32 653 ..
+  //                    252 709 129 368 440 314 287 854 460 594 512 239 719 751 ..
+  //                    708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850;
+  //                    //Constraint 3
+  //                    806 361 199 781 596 669 957 358 259 888 319 751 275 177 ..
+  //                    883 749 229 265 282 694 819 77 190 551 140 442 867 283 ..
+  //                    137 359 445 58 440 192 485 744 844 969 50 833 57 877 ..
+  //                    482 732 968 113 486 710 439 747 174 260 877 474 841 422 ..
+  //                    280 684 330 910 791 322 404 403 519 148 948 414 894 147 ..
+  //                    73 297 97 651 380 67 582 973 143 732 624 518 847 113 ..
+  //                    382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ;
+  //                    //Constraint 4
+  //                    404 197 817 1000 44 307 39 659 46 334 448 599 931 776 ..
+  //                    263 980 807 378 278 841 700 210 542 636 388 129 203 110 ..
+  //                    817 502 657 804 662 989 585 645 113 436 610 948 919 115 ..
+  //                    967 13 445 449 740 592 327 167 368 335 179 909 825 614 ..
+  //                    987 350 179 415 821 525 774 283 427 275 659 392 73 896 ..
+  //                    68 982 697 421 246 672 649 731 191 514 983 886 95 846 ..
+  //                    689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322;
+  //                    //Constrain 5
+  //                    475 36 287 577 45 700 803 654 196 844 657 387 518 143 ..
+  //                    515 335 942 701 332 803 265 922 908 139 995 845 487 100 ..
+  //                    447 653 649 738 424 475 425 926 795 47 136 801 904 740 ..
+  //                    768 460 76 660 500 915 897 25 716 557 72 696 653 933 ..
+  //                    420 582 810 861 758 647 237 631 271 91 75 756 409 440 ..
+  //                    483 336 765 637 981 980 202 35 594 689 602 76 767 693 ..
+  //                    893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ;
+  //     ];
+  //    nbVar = size(objCoef,2)
+  //    conUB=[11927 13727 11551 13056 13460 ];
+  //    // Lower Bound of variables
+  //    lb = repmat(0,1,nbVar)
+  //    // Upper Bound of variables
+  //    ub = repmat(1,1,nbVar)
+  //    // Lower Bound of constrains
+  //    intcon = []
+  //    for i = 1:nbVar
+  //        intcon = [intcon i];
+  //    end
+  //    options = list("time_limit", 25);
+  //    // The expected solution :
+  //    // Output variables
+  //    xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 ..
+  //            0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 ..
+  //            0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0]
+  //    // Optimal value
+  //    fopt = [ 24381 ]
+  //    // Calling Symphony
+  //    [x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options);
+  // 
+  // 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 < 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
+   
+   
+   objCoef = varargin(1)
+   intcon = varargin(2)
+   A = varargin(3)
+   b = varargin(4)
+   
+   nbVar = size(objCoef,2);
+   nbCon = size(A,1);
+   
+   if ( rhs<4 ) then
+      Aeq = []
+      beq = []
+   else
+      Aeq = varargin(5);
+      beq = varargin(6);
+      
+      if (size(Aeq,1)~=0) then
+           //Check the size of equality constraint which should equal to the number of inequality constraints
+            if ( size(Aeq,2) ~= nbVar) then
+                errmsg = msprintf(gettext("%s: The size of equality constraint is not equal to the number of variables"), "Symphony");
+                error(errmsg);
+            end
+          
+          //Check the size of upper bound of inequality constraint which should equal to the number of constraints
+            if ( size(beq,2) ~= size(Aeq,1)) then
+                errmsg = msprintf(gettext("%s: The equality constraint upper bound is not equal to the number of equality constraint"), "Symphony");
+                error(errmsg);
+            end
+      end
+      
+   end
+   
+   if ( rhs<6 ) then
+      lb = repmat(-%inf,1,nbVar);
+      ub = repmat(%inf,1,nbVar);
+   else
+      lb = varargin(7);
+      ub = varargin(8);
+   end
+   
+   if (rhs<8) then
+      options = list();
+   else
+      options = varargin(9);
+   end
+   
+
+//Check the size of lower bound of inequality constraint which should equal to the number of constraints
+   if ( size(b,2) ~= size(A,1)) then
+      errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraint is not equal to the number of constraint"), "Symphony");
+      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"), "Symphony");
+      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"), "Symphony");
+      error(errmsg);
+   end
+   
+    //Changing the inputs in symphony's format 
+    conMatrix = [A;Aeq]
+    nbCon = size(conMatrix,1);
+    conLB = [repmat(-%inf,1,size(A,1)), beq]';
+    conUB = [b,beq]' ; 
+    
+    isInt = repmat(%f,1,nbVar);
+    for i=1:size(intcon,2)
+        isInt(intcon(i)) = %t
+    end
+    
+    objSense = 1;
+    
+   [xopt,fopt,status,iter] = symphony_call(nbVar,nbCon,objCoef,isInt,lb,ub,conMatrix,conLB,conUB,objSense,options);
+
+endfunction
-- 
cgit