Bugs fixed 4

12 files changed, 427 insertions, 378 deletions

diff --git a/macros/lsqlin.bin b/macros/lsqlin.bin
index ce5d4a4..8c30789 100644
--- a/macros/lsqlin.bin
+++ b/macros/lsqlin.bin
diff --git a/macros/lsqlin.sci b/macros/lsqlin.sci
index 08554e1..fba036d 100644
--- a/macros/lsqlin.sci
+++ b/macros/lsqlin.sci
@@ -22,22 +22,22 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	//   [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin( ... )
 	//   
 	//   Parameters
-	//   C : a matrix of double, represents the multiplier of the solution x in the expression C*x - d. C is M-by-N, where M is the number of equations, and N is the number of elements of x.
-	//   d : a vector of double, represents the additive constant term in the expression C*x - d. d is M-by-1, where M is the number of equations.
+	//   C : a matrix of double, represents the multiplier of the solution x in the expression C*x - d. Number of columns in C is equal to the number of elements in x.
+	//   d : a vector of double, represents the additive constant term in the expression C*x - d. Number of elements in d is equal to the number of rows in C matrix.
 	//   A : a vector of double, represents the linear coefficients in the inequality constraints
 	//   b : a vector of double, represents the linear coefficients in the inequality constraints
 	//   Aeq : a matrix of double, represents the linear coefficients in the equality constraints
 	//   beq : a vector of double, represents the linear coefficients in the equality constraints
-	//   LB : a vector of double, contains lower bounds of the variables.
-	//   UB : a vector of double,  contains upper bounds of the variables.
+	//   lb : a vector of double, contains lower bounds of the variables.
+	//   ub : a vector of double,  contains upper bounds of the variables.
 	//   x0 : a vector of double, contains initial guess of variables.
 	//   param : a list containing the the parameters to be set.
 	//   xopt : a vector of double, the computed solution of the optimization problem.
 	//   resnorm : a double, objective value returned as the scalar value norm(C*x-d)^2.
 	//   residual : a vector of double, solution residuals returned as the vector C*x-d.
-	//   exitflag : Integer identifying the reason the algorithm terminated.
-	//   output : Structure containing information about the optimization. Right now it contains number of iteration.
-	//   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.
+	//   exitflag : Integer identifying the reason the algorithm terminated. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the lsqlin macro. 
+	//   output : Structure containing information about the optimization. This version only contains number of iterations.
+	//   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper bound multiplier and linear equality, inequality constraints.
 	//   
 	//   Description
 	//   Search the minimum of a constrained linear least square problem specified by :
@@ -45,14 +45,14 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	//   <latex>
 	//    \begin{eqnarray}
 	//    &\mbox{min}_{x}
-	//    & 1/2||C*x - d||_2^2  \\
-	//    & \text{subject to} & A*x \leq b \\
-	//    & & Aeq*x = beq \\
+	//    & 1/2||C⋅x - d||_2^2  \\
+	//    & \text{subject to} & A⋅x \leq b \\
+	//    & & Aeq⋅x = beq \\
 	//    & & lb \leq x \leq ub \\
 	//    \end{eqnarray}
 	//   </latex>
 	//   
-	//   We are calling IPOpt for solving the linear least square problem, IPOpt is a library written in C++.
+	//   The routine calls Ipopt for solving the linear least square problem, Ipopt is a library written in C++.
 	//
 	// Examples
 	// //A simple linear least square example
@@ -76,7 +76,7 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	// // Press ENTER to continue 
 	//    
 	// Examples
-	// //A basic example for equality, inequality and bounds
+	// //A basic example for equality, inequality constraints and variable bounds
 	// C = [0.9501    0.7620    0.6153    0.4057
 	//     0.2311    0.4564    0.7919    0.9354
 	//     0.6068    0.0185    0.9218    0.9169
@@ -111,11 +111,22 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 		error(errmsg)
 	end
 
+// Initializing all the values to empty matrix
+	C=[];
+	d=[];
+	A=[];
+	b=[];
+	Aeq=[];
+	beq=[];
+	lb=[];
+	ub=[];
+	x0=[];
+
 	C = varargin(1);
 	d = varargin(2);
 	A = varargin(3);
 	b = varargin(4);
-	nbVar = size(C,2);
+	nbVar = size(C,2);	
 
 	if ( rhs<5 ) then
 		Aeq = []
@@ -126,11 +137,11 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	end
 
 	if ( rhs<7 ) then
-		LB = repmat(-%inf,nbVar,1);
-		UB = repmat(%inf,nbVar,1);
+		lb = repmat(-%inf,nbVar,1);
+		ub = repmat(%inf,nbVar,1);
 	else
-		LB = varargin(7);
-		UB = varargin(8);
+		lb = varargin(7);
+		ub = varargin(8);
 	end
 
 
@@ -146,12 +157,12 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 		param =varargin(10);
 	end
 
-	if (size(LB,2)==0) then
-		LB = repmat(-%inf,nbVar,1);
+	if (size(lb,2)==0) then
+		lb = repmat(-%inf,nbVar,1);
 	end
 
-	if (size(UB,2)==0) then
-		UB = repmat(%inf,nbVar,1);
+	if (size(ub,2)==0) then
+		ub = repmat(%inf,nbVar,1);
 	end
 
 	if (type(param) ~= 15) then
@@ -193,12 +204,12 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 		d=d';
 	end
 
-	if (size(LB,2)== [nbVar]) then
-		LB = LB';
+	if (size(lb,2)== [nbVar]) then
+		lb = lb';
 	end
 
-	if (size(UB,2)== [nbVar]) then
-		UB = UB';
+	if (size(ub,2)== [nbVar]) then
+		ub = ub';
 	end
 
 	if (size(b,2)==nbConInEq) then
@@ -221,7 +232,7 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 
 	//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 number of columns in A must be the same as the number of elements of d"), "lsqlin");
+		errmsg = msprintf(gettext("%s: The number of columns in A must be the same as the number of columns in C"), "lsqlin");
 		error(errmsg);
 	end
 
@@ -232,20 +243,20 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	end
 
 	//Check the size of Lower Bound which should be equal to the number of variables
-	if ( size(LB,1) ~= nbVar) then
+	if ( size(lb,1) ~= nbVar) then
 		errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "lsqlin");
 		error(errmsg);
 	end
 
 	//Check the size of Upper Bound which should equal to the number of variables
-	if ( size(UB,1) ~= nbVar) then
+	if ( size(ub,1) ~= nbVar) then
 		errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "lsqlin");
 		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 number of rows in A must be the same as the number of elementsof b"), "lsqlin");
+		errmsg = msprintf(gettext("%s: The number of rows in A must be the same as the number of elements of b"), "lsqlin");
 		error(errmsg);
 	end
 
@@ -259,6 +270,7 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	if ( size(x0,1) ~= nbVar) then
 		warnmsg = msprintf(gettext("%s: Ignoring initial guess of variables as it is not equal to the number of variables"), "lsqlin");
 		warning(warnmsg);
+		x0 = repmat(0,nbVar,1);
 	end
 
 	//Check if the user gives a matrix instead of a vector
@@ -268,12 +280,12 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 		error(errmsg); 
 	end
 
-	if (size(LB,1)~=1)& (size(LB,2)~=1) then
+	if (size(lb,1)~=1)& (size(lb,2)~=1) then
 		errmsg = msprintf(gettext("%s: Lower Bound should be a vector"), "lsqlin");
 		error(errmsg); 
 	end
 
-	if (size(UB,1)~=1)& (size(UB,2)~=1) then
+	if (size(ub,1)~=1)& (size(ub,2)~=1) then
 		errmsg = msprintf(gettext("%s: Upper Bound should be a vector"), "lsqlin");
 		error(errmsg); 
 	end
@@ -294,31 +306,31 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 
 	for i = 1:nbConInEq
 		if (b(i) == -%inf)
-		   	errmsg = msprintf(gettext("%s: Value of b can not be negative infinity"), "qpipoptmat");
+		   	errmsg = msprintf(gettext("%s: Value of b can not be negative infinity"), "lsqlin");
             error(errmsg); 
         end	
 	end
     
 	for i = 1:nbConEq
 		if (beq(i) == -%inf)
-		   	errmsg = msprintf(gettext("%s: Value of beq can not be negative infinity"), "qpipoptmat");
+		   	errmsg = msprintf(gettext("%s: Value of beq can not be negative infinity"), "lsqlin");
             error(errmsg); 
         end	
 	end
 
 	//Converting it into Quadratic Programming Problem
 
-	Q = C'*C;
-	p = [-C'*d]';
+	H = C'*C;
+	f = [-C'*d]';
 	op_add = d'*d;
-	LB = LB';
-	UB = UB';
+	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,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options);
+	[xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,lb,ub,x0,options);
 
 	xopt = xopt';
 	residual = -1*(C*xopt-d);
@@ -326,15 +338,15 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 	exitflag = status;
 	output = struct("Iterations"      , []);
 	output.Iterations = iter;
-   lambda = struct("lower"           , [], ..
-                   "upper"           , [], ..
-                   "eqlin"           , [], ..
+	lambda = struct("lower"           , [], ..
+		           "upper"           , [], ..
+		           "eqlin"           , [], ..
 				   "ineqlin"         , []);
-   
-   lambda.lower = Zl;
-   lambda.upper = Zu;
-   lambda.eqlin = lmbda(1:nbConEq);
-   lambda.ineqlin = lmbda(nbConEq+1:nbCon);
+
+	lambda.lower = Zl;
+	lambda.upper = Zu;
+	lambda.eqlin = lmbda(1:nbConEq);
+	lambda.ineqlin = lmbda(nbConEq+1:nbCon);
 
 	select status 
 		case 0 then
@@ -362,11 +374,11 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
 		case 12 then
 			printf("\nProblem has too few degrees of freedom.\n");
 		case 13 then
-			printf("\nInvalid option thrown back by IPOpt\n");
+			printf("\nInvalid option thrown back by Ipopt\n");
 		case 14 then
 			printf("\nNot enough memory.\n");
 		case 15 then
-			printf("\nINTERNAL ERROR: Unknown SolverReturn value - Notify IPOPT Authors.\n");
+			printf("\nINTERNAL ERROR: Unknown SolverReturn value - Notify Ipopt Authors.\n");
 		else
 			printf("\nInvalid status returned. Notify the Toolbox authors\n");
 		break;
diff --git a/macros/lsqnonneg.bin b/macros/lsqnonneg.bin
index 84e307b..182cfa9 100644
--- a/macros/lsqnonneg.bin
+++ b/macros/lsqnonneg.bin
diff --git a/macros/lsqnonneg.sci b/macros/lsqnonneg.sci
index b8694b4..5f6ffa2 100644
--- a/macros/lsqnonneg.sci
+++ b/macros/lsqnonneg.sci
@@ -19,14 +19,14 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 	//   [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg( ... )
 	//   
 	//   Parameters
-	//   C : a matrix of doubles, represents the multiplier of the solution x in the expression C*x - d. C is M-by-N, where M is the number of equations, and N is the number of elements of x.
-	//   d : a vector of doubles, represents the additive constant term in the expression C*x - d. d is M-by-1, where M is the number of equations.
-	//   xopt : a vector of doubles, the computed solution of the optimization problem.
+	//   C : a matrix of double, represents the multiplier of the solution x in the expression C*x - d. Number of columns in C is equal to the number of elements in x.
+	//   d : a vector of double, represents the additive constant term in the expression C*x - d. Number of elements in d is equal to the number of rows in C matrix.
+	//   xopt : a vector of double, the computed solution of the optimization problem.
 	//   resnorm : a double, objective value returned as the scalar value norm(C*x-d)^2.
-	//   residual : a vector of doubles, solution residuals returned as the vector C*x-d.
-	//   exitflag : Integer identifying the reason the algorithm terminated.
-	//   output : Structure containing information about the optimization. Right now it contains number of iteration.
-	//   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.
+	//   residual : a vector of double, solution residuals returned as the vector C*x-d.
+	//   exitflag : Integer identifying the reason the algorithm terminated. It could be 0, 1 or 2 i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded.
+	//   output : Structure containing information about the optimization. This version only contains number of iterations.
+	//   lambda : Structure containing the Lagrange multipliers at the solution x. It contains lower and upper bound multiplier.
 	//   
 	//   Description
 	//   Solves nonnegative least-squares curve fitting problems specified by :
@@ -34,12 +34,12 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 	//   <latex>
 	//    \begin{eqnarray}
 	//    &\mbox{min}_{x}
-	//    & 1/2||C*x - d||_2^2  \\
+	//    & 1/2||C⋅x - d||_2^2  \\
 	//    & & x \geq 0 \\
 	//    \end{eqnarray}
 	//   </latex>
 	//   
-	//   We are calling IPOpt for solving the nonnegative least-squares curve fitting problems, IPOpt is a library written in C++.
+	//   The routine calls Ipopt for solving the nonnegative least-squares curve fitting problems, Ipopt is a library written in C++.
 	//    
 	// Examples 
 	// // A basic lsqnonneg problem
@@ -63,7 +63,7 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 
 	//To check the number of argument given by user
 	if ( rhs < 2 | rhs > 3 ) then
-		errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 3]"), "lsqlin", rhs);
+		errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 3]"), "lsqnonneg", rhs);
 		error(errmsg)
 	end
 
@@ -73,21 +73,21 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 	if ( rhs<3 | size(varargin(3)) ==0 ) then
 		param = list();
 	else
-		param =varargin(10);
+		param =varargin(3);
 	end
 
 	if (type(param) ~= 15) then
-		errmsg = msprintf(gettext("%s: param should be a list "), "lsqlin");
+		errmsg = msprintf(gettext("%s: param should be a list "), "lsqnonneg");
 		error(errmsg);
 	end
 
 
 	if (modulo(size(param),2)) then
-		errmsg = msprintf(gettext("%s: Size of parameters should be even"), "lsqlin");
+		errmsg = msprintf(gettext("%s: Size of parameters should be even"), "lsqnonneg");
 		error(errmsg);
 	end
 
-	options = list(	"MaxIter"     , [3000], ...
+	options = list(	"MaxIter"   , [3000], ...
 					"CpuTime"   , [600] ...
 	);
 
@@ -99,7 +99,7 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 			case "CpuTime" then
 				options(2*i) = param(2*i);
 			else
-				errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "lsqlin", param(2*i-1));
+				errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "lsqnonneg", param(2*i-1));
 				error(errmsg)
 		end
 	end
@@ -114,7 +114,7 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 
 	//Check the size of f which should equal to the number of variable
 	if ( size(d,1) ~= size(C,1)) then
-		errmsg = msprintf(gettext("%s: The number of rows in C must be equal the number of elements of d"), "lsqlin");
+		errmsg = msprintf(gettext("%s: The number of rows in C must be equal the number of elements of d"), "lsqnonneg");
 		error(errmsg);
 	end
 
@@ -123,14 +123,14 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 	Q = C'*C;
 	p = [-C'*d]';
 	op_add = d'*d;
-	LB = repmat(0,1,nbVar);
-	UB = repmat(%inf,1,nbVar);	
+	lb = repmat(0,1,nbVar);
+	ub = repmat(%inf,1,nbVar);	
 	x0 = repmat(0,1,nbVar);;
 	conMatrix = [];
 	nbCon = size(conMatrix,1);
 	conLB = [];
 	conUB = [] ; 
-	[xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options);
+	[xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,lb,ub,x0,options);
 
 	xopt = xopt';
 	residual = -1*(C*xopt-d);
@@ -170,11 +170,11 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
 		case 12 then
 			printf("\nProblem has too few degrees of freedom.\n");
 		case 13 then
-			printf("\nInvalid option thrown back by IPOpt\n");
+			printf("\nInvalid option thrown back by Ipopt\n");
 		case 14 then
 			printf("\nNot enough memory.\n");
 		case 15 then
-			printf("\nINTERNAL ERROR: Unknown SolverReturn value - Notify IPOPT Authors.\n");
+			printf("\nINTERNAL ERROR: Unknown SolverReturn value - Notify Ipopt Authors.\n");
 		else
 			printf("\nInvalid status returned. Notify the Toolbox authors\n");
 		break;
diff --git a/macros/qpipopt.bin b/macros/qpipopt.bin
index f4b14b9..4a407c4 100644
--- a/macros/qpipopt.bin
+++ b/macros/qpipopt.bin
diff --git a/macros/qpipopt.sci b/macros/qpipopt.sci
index 6a53693..ed531e1 100644
--- a/macros/qpipopt.sci
+++ b/macros/qpipopt.sci
@@ -14,27 +14,27 @@ 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 = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB)
+  //   xopt = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0)
+  //   xopt = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0,param)
   //   [xopt,fopt,exitflag,output,lamda] = qpipopt( ... )
   //   
   //   Parameters
   //   nbVar : a double, number of variables
   //   nbCon : a double, number of constraints
-  //   Q : a symmetric matrix of double, represents coefficients of quadratic in the quadratic problem.
-  //   p : a vector of double, represents coefficients of linear in the quadratic problem
-  //   LB : a vector of double, contains lower bounds of the variables.
-  //   UB : a vector of double, contains upper bounds of the variables.
-  //   conMatrix : a matrix of double, contains  matrix representing the constraint matrix 
+  //   H : a symmetric matrix of double, represents coefficients of quadratic in the quadratic problem.
+  //   f : a vector of double, represents coefficients of linear in the quadratic problem
+  //   lb : a vector of double, contains lower bounds of the variables.
+  //   ub : a vector of double, contains upper bounds of the variables.
+  //   A : a matrix of double, contains  matrix representing the constraint matrix 
   //   conLB : a vector of double, contains lower bounds of the constraints. 
   //   conUB : a vector of double, contains upper bounds of the constraints. 
   //   x0 : a vector of double, contains initial guess of variables.
   //   param : a list containing the the parameters to be set.
   //   xopt : a vector of double, the computed solution of the optimization problem.
   //   fopt : a double, the function value at x.
-  //   exitflag : Integer identifying the reason the algorithm terminated.
-  //   output : Structure containing information about the optimization. Right now it contains number of iteration.
+  //   exitflag : Integer identifying the reason the algorithm terminated. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the qpipopt macro.
+  //   output : Structure containing information about the optimization. This version only contains number of iterations
   //   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.
   //   
   //   Description
@@ -44,32 +44,32 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //   <latex>
   //    \begin{eqnarray}
   //    &\mbox{min}_{x}
-  //    & 1/2*x'*Q*x + p'*x  \\
-  //    & \text{subject to} & conLB \leq C(x) \leq conUB \\
+  //    & 1/2⋅x^T⋅H⋅x + f^T⋅x  \\
+  //    & \text{subject to} & conLB \leq A⋅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 routine calls Ipopt for solving the quadratic problem, Ipopt is a library written in C++.
   //
   // 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];
+  //      A= [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);
+  //      //and minimize 0.5*x'⋅H⋅x + f'⋅x with
+  //      f=[1; 2; 3; 4; 5; 6]; H=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)
+  //      [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0,param)
   // // Press ENTER to continue
   //    
   // Examples 
@@ -80,16 +80,16 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
   //    // –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];
+  //	H = [1 -1; -1 2]; 
+  //	f = [-2; -6];
+  //    A = [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)
+  //	[xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB)
   // Authors
   // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
     
@@ -103,35 +103,43 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
     error(errmsg)
    end
    
+	nbVar = [];
+	nbCon = [];
+	H = [];
+	f = [];
+	A = [];
+	conLB = [];
+	conUB = [];
+	lb = [];
+	ub = [];
    
-   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);
+	nbVar = varargin(1);
+	nbCon = varargin(2);
+	H = varargin(3);
+	f = varargin(4);
+	lb = varargin(5);
+	ub = varargin(6);
+	A = varargin(7);
+	conLB = varargin(8);
+	conUB = varargin(9);
 
-    if (size(LB,2)==0) then
-        LB = repmat(-%inf,nbVar,1);
+    if (size(lb,2)==0) then
+        lb = repmat(-%inf,nbVar,1);
     end
     
-    if (size(UB,2)==0) then
-        UB = repmat(%inf,nbVar,1);
+    if (size(ub,2)==0) then
+        ub = repmat(%inf,nbVar,1);
     end
 
-    if (size(p,2)==0) then
-        p = repmat(0,nbVar,1);
+    if (size(f,2)==0) then
+        f = repmat(0,nbVar,1);
     end
     
-    
-   if ( rhs<10 | size(varargin(10)) ==0 ) then
-      x0 = repmat(0,nbVar,1);
-   else
-      x0 = varargin(10);
-  end
+	if ( rhs<10 | size(varargin(10)) ==0 ) then
+		x0 = repmat(0,nbVar,1);
+	else
+		x0 = varargin(10);
+	end
    
    if ( rhs<11 | size(varargin(11)) ==0 ) then
       param = list(); 
@@ -144,11 +152,10 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
       error(errmsg);
    end
    
-   if (modulo(size(param),2)) then
-	errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipopt");
-	error(errmsg);
-   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], ...
@@ -171,16 +178,16 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
 // Check if the user gives row vector 
 // and Changing it to a column matrix
 
-   if (size(p,2)== [nbVar]) then
-   	p=p';
-   end
+	if (size(f,2)== [nbVar]) then
+		f=f';
+	end
 
-   if (size(LB,2)== [nbVar]) then
-	LB = LB';
-   end
+	if (size(lb,2)== [nbVar]) then
+		lb = lb';
+	end
 
-   if (size(UB,2)== [nbVar]) then
-      UB = UB';
+   if (size(ub,2)== [nbVar]) then
+      ub = ub';
    end
 
    if (size(conUB,2)== [nbCon]) then
@@ -196,53 +203,53 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
    end
 
    //IPOpt wants it in row matrix form
-   p = p';
-   LB = LB';
-   UB = UB';
+   f = f';
+   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");
+   //Checking the H matrix which needs to be a symmetric matrix
+   if ( ~isequal(H,H') ) then
+      errmsg = msprintf(gettext("%s: H 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");
+   //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 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");
+   if ( size(f,2) ~= [nbVar]) then
+      errmsg = msprintf(gettext("%s: The Size of f is not equal to the number of variables"), "qpipopt");
       error(errmsg);
    end
    
    if (nbCon) then
           //Check the size of constraint which should equal to the number of variables
-       if ( size(conMatrix,2) ~= nbVar) then
+       if ( size(A,2) ~= nbVar) then
           errmsg = msprintf(gettext("%s: The size of constraints is not equal to the number of variables"), "qpipopt");
           error(errmsg);
        end
    end
 
    //Check the number of constraint
-   if ( size(conMatrix,1) ~= nbCon) then
+   if ( size(A,1) ~= nbCon) then
       errmsg = msprintf(gettext("%s: The size of constraint matrix is not equal to the number of constraint given i.e. %d"), "qpipopt", nbCon);
       error(errmsg);
    end
 
    //Check the size of Lower Bound which should equal to the number of variables
-   if ( size(LB,2) ~= nbVar) then
+   if ( size(lb,2) ~= nbVar) then
       errmsg = msprintf(gettext("%s: The size of 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
+   if ( size(ub,2) ~= nbVar) then
       errmsg = msprintf(gettext("%s: The size of Upper Bound is not equal to the number of variables"), "qpipopt");
       error(errmsg);
    end
@@ -263,21 +270,22 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
    if ( size(x0,2) ~= nbVar | size(x0,"*")>nbVar) then
       warnmsg = msprintf(gettext("%s: Ignoring initial guess of variables as it is not equal to the number of variables"), "qpipopt");
       warning(warnmsg);
+	  x0 = repmat(0,1,nbVar);
    end
    
    //Check if the user gives a matrix instead of a vector
    
-   if ((size(p,1)~=1)& (size(p,2)~=1)) then
-      errmsg = msprintf(gettext("%s: p should be a vector"), "qpipopt");
+   if ((size(f,1)~=1)& (size(f,2)~=1)) then
+      errmsg = msprintf(gettext("%s: f should be a vector"), "qpipopt");
       error(errmsg); 
    end
    
-   if (size(LB,1)~=1)& (size(LB,2)~=1) then
+   if (size(lb,1)~=1)& (size(lb,2)~=1) then
       errmsg = msprintf(gettext("%s: Lower Bound should be a vector"), "qpipopt");
       error(errmsg); 
    end
    
-   if (size(UB,1)~=1)& (size(UB,2)~=1) then
+   if (size(ub,1)~=1)& (size(ub,2)~=1) then
       errmsg = msprintf(gettext("%s: Upper Bound should be a vector"), "qpipopt");
       error(errmsg); 
    end
@@ -307,7 +315,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
 		end	
 	end
 
-   [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options);
+   [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,A,conLB,conUB,lb,ub,x0,options);
    
    xopt = xopt';
    exitflag = status;
@@ -348,11 +356,11 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
     case 12 then
         printf("\nProblem has too few degrees of freedom.\n");
     case 13 then
-        printf("\nInvalid option thrown back by IPOpt\n");
+        printf("\nInvalid option thrown back by Ipopt\n");
     case 14 then
         printf("\nNot enough memory.\n");
     case 15 then
-        printf("\nINTERNAL ERROR: Unknown SolverReturn value - Notify IPOPT Authors.\n");
+        printf("\nINTERNAL ERROR: Unknown SolverReturn value - Notify Ipopt Authors.\n");
     else
         printf("\nInvalid status returned. Notify the Toolbox authors\n");
         break;
diff --git a/macros/qpipoptmat.bin b/macros/qpipoptmat.bin
index 89ce559..35142ae 100644
--- a/macros/qpipoptmat.bin
+++ b/macros/qpipoptmat.bin
diff --git a/macros/qpipoptmat.sci b/macros/qpipoptmat.sci
index e9ed9a5..8e9c67e 100644
--- a/macros/qpipoptmat.sci
+++ b/macros/qpipoptmat.sci
@@ -29,14 +29,14 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
 	//   b : a vector of double, represents the linear coefficients in the inequality constraints
 	//   Aeq : a matrix of double, represents the linear coefficients in the equality constraints
 	//   beq : a vector of double, represents the linear coefficients in the equality constraints
-	//   LB : a vector of double, contains lower bounds of the variables.
-	//   UB : a vector of double, contains upper bounds of the variables.
+	//   lb : a vector of double, contains lower bounds of the variables.
+	//   ub : a vector of double, contains upper bounds of the variables.
 	//   x0 : a vector of double, contains initial guess of variables.
 	//   param : a list containing the the parameters to be set.
 	//   xopt : a vector of double, the computed solution of the optimization problem.
 	//   fopt : a double, the function value at x.
-	//   exitflag : Integer identifying the reason the algorithm terminated.
-	//   output : Structure containing information about the optimization. Right now it contains number of iteration.
+	//   exitflag : Integer identifying the reason the algorithm terminated.It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the qpipoptmat macro.
+	//   output : Structure containing information about the optimization. This version only contains number of iterations.
 	//   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.
 	//   
 	//   Description
@@ -46,14 +46,14 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
 	//   <latex>
 	//    \begin{eqnarray}
 	//    &\mbox{min}_{x}
-	//    & 1/2*x'*H*x + f'*x  \\
-	//    & \text{subject to} & A*x \leq b \\
-	//    & & Aeq*x = beq \\
+	//    & 1/2⋅x^T⋅H⋅x + f^T⋅x  \\
+	//    & \text{subject to} & A⋅x \leq b \\
+	//    & & Aeq⋅x = beq \\
 	//    & & lb \leq x \leq ub \\
 	//    \end{eqnarray}
 	//   </latex>
 	//   
-	//   We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++.
+	//   The routine calls Ipopt for solving the quadratic problem, Ipopt is a library written in C++.
 	//
 	// Examples
 	//    //Find the value of x that minimize following function
@@ -101,9 +101,18 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
     error(errmsg)
    end
    
-   H = varargin(1);
-   f = varargin(2);
-   nbVar = size(H,1);
+	H = [];
+	f = [];
+	A = [];
+	b = [];
+	Aeq = [];
+	beq = []; 
+	lb = [];
+	ub = [];
+
+	H = varargin(1);
+	f = varargin(2);
+	nbVar = size(H,1);
 
    
    if ( rhs<3 ) then
@@ -123,11 +132,11 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
   end
   
   if ( rhs<7 ) then
-      LB = repmat(-%inf,nbVar,1);
-      UB = repmat(%inf,nbVar,1);
+      lb = repmat(-%inf,nbVar,1);
+      ub = repmat(%inf,nbVar,1);
    else
-      LB = varargin(7);
-      UB = varargin(8);
+      lb = varargin(7);
+      ub = varargin(8);
   end
 
 
@@ -143,12 +152,12 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
       param =varargin(10);
    end
    
-   if (size(LB,2)==0) then
-        LB = repmat(-%inf,nbVar,1);
+   if (size(lb,2)==0) then
+        lb = repmat(-%inf,nbVar,1);
     end
     
-    if (size(UB,2)==0) then
-        UB = repmat(%inf,nbVar,1);
+    if (size(ub,2)==0) then
+        ub = repmat(%inf,nbVar,1);
     end
 
     if (size(f,2)==0) then
@@ -195,12 +204,12 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
       f=f';
    end
 
-   if (size(LB,2)== [nbVar]) then
-	LB = LB';
+   if (size(lb,2)== [nbVar]) then
+	lb = lb';
    end
 
-   if (size(UB,2)== [nbVar]) then
-	UB = UB';
+   if (size(ub,2)== [nbVar]) then
+	ub = ub';
    end
 
    if (size(b,2)==nbConInEq) then
@@ -228,7 +237,6 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
       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 number of columns in A must be the same as the number of elements of f"), "qpipoptmat");
@@ -243,13 +251,13 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
 
 
    //Check the size of Lower Bound which should be equal to the number of variables
-   if ( size(LB,1) ~= nbVar) then
+   if ( size(lb,1) ~= nbVar) then
       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
-   if ( size(UB,1) ~= nbVar) then
+   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
@@ -270,6 +278,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
    if ( size(x0,1) ~= nbVar) then
       warnmsg = msprintf(gettext("%s: Ignoring initial guess of variables as it is not equal to the number of variables"), "qpipoptmat");
       warning(warnmsg);
+	  x0 = repmat(0,nbVar,1);
    end
    
    //Check if the user gives a matrix instead of a vector
@@ -279,12 +288,12 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
       error(errmsg); 
    end
    
-   if (size(LB,1)~=1)& (size(LB,2)~=1) then
+   if (size(lb,1)~=1)& (size(ub,2)~=1) then
       errmsg = msprintf(gettext("%s: Lower Bound should be a vector"), "qpipoptmat");
       error(errmsg); 
    end
    
-   if (size(UB,1)~=1)& (size(UB,2)~=1) then
+   if (size(ub,1)~=1)& (size(ub,2)~=1) then
       errmsg = msprintf(gettext("%s: Upper Bound should be a vector"), "qpipoptmat");
       error(errmsg); 
    end
@@ -319,14 +328,14 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
    
    //Converting it into ipopt format
    f = f';
-   LB = LB';
-   UB = UB';
+   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,x0,options);
+   [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,lb,ub,x0,options);
    
    xopt = xopt';
    exitflag = status;
@@ -369,11 +378,11 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
     case 12 then
         printf("\nProblem has too few degrees of freedom.\n");
     case 13 then
-        printf("\nInvalid option thrown back by IPOpt\n");
+        printf("\nInvalid option thrown back by Ipopt\n");
     case 14 then
         printf("\nNot enough memory.\n");
     case 15 then
-        printf("\nINTERNAL ERROR: Unknown SolverReturn value - Notify IPOPT Authors.\n");
+        printf("\nINTERNAL ERROR: Unknown SolverReturn value - Notify Ipopt Authors.\n");
     else
         printf("\nInvalid status returned. Notify the Toolbox authors\n");
         break;
diff --git a/macros/symphony.bin b/macros/symphony.bin
index 562f5cc..9217660 100644
--- a/macros/symphony.bin
+++ b/macros/symphony.bin
diff --git a/macros/symphony.sci b/macros/symphony.sci
index cc05dcd..264a513 100644
--- a/macros/symphony.sci
+++ b/macros/symphony.sci
@@ -13,27 +13,27 @@ 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 = symphony(nbVar,nbCon,c,isInt,lb,ub,A,conLB,conUB)
+	//   xopt = symphony(nbVar,nbCon,c,isInt,lb,ub,A,conLB,conUB,objSense)
+	//   xopt = symphony(nbVar,nbCon,c,isInt,lb,ub,A,conLB,conUB,objSense,options)
 	//   [xopt,fopt,status,output] = symphony( ... )
 	//   
 	//   Parameters
 	//   nbVar : a double, number of variables.
 	//   nbCon : a double, number of constraints.
-	//   objCoeff : a vector of double, represents coefficients of the variables in the objective.
+	//   c : a vector of double, represents coefficients of the variables in the objective.
 	//   isInt : a vector of boolean, represents wether a variable is constrained to be an integer.
-	//   LB : a vector of double, represents lower bounds of the variables.
-	//   UB : a vector of double, represents upper bounds of the variables.
-	//   conMatrix : a matrix of double, represents  matrix representing the constraint matrix.
+	//   lb : a vector of double, represents lower bounds of the variables.
+	//   ub : a vector of double, represents upper bounds of the variables.
+	//   A : a matrix of double, represents  matrix representing the constraint matrix.
 	//   conLB : a vector of double, represents lower bounds of the constraints. 
 	//   conUB : a vector of double, represents upper bounds of the constraints
 	//   objSense : The sense (maximization/minimization) of the objective. Use 1(sym_minimize ) or -1 (sym_maximize) here.
-	//   options : a a list containing the the parameters to be set.
+	//   options : a list containing the the parameters to be set.
 	//   xopt : a vector of double, the computed solution of the optimization problem.
 	//   fopt : a double, the function value at x.
-	//   status : status flag from symphony.
-	//   output : The output data structure contains detailed informations about the optimization process. Right now it contains number of iteration.
+	//   status : status flag from symphony. 227 is optimal, 228 is Time limit exceeded, 230 is iteration limit exceeded.
+	//   output : The output data structure contains detailed information about the optimization process. This version only contains number of iterations
 	//   
 	//   Description
 	//   Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
@@ -42,37 +42,37 @@ function [xopt,fopt,status,output] = symphony (varargin)
 	//   <latex>
 	//    \begin{eqnarray}
 	//    &\mbox{min}_{x}
-	//    & f^T*x \\
-	//    & \text{subject to} & conLB \leq C*x \leq conUB \\
+	//    & f^T⋅x \\
+	//    & \text{subject to} & conLB \leq A⋅x \leq conUB \\
 	//    & & lb \leq x \leq ub \\
 	//    & & x_i \in \!\, \mathbb{Z}, i \in \!\, I
 	//    \end{eqnarray}
 	//   </latex>
 	//   
-	//   We are calling SYMPHONY written in C by gateway files for the actual computation.
+	//   The routine calls SYMPHONY written in C by gateway files for the actual computation.
 	//
 	//   Examples
 	//    //A basic case : 
 	//    // Objective function
-	//    objCoef = [350*5,330*3,310*4,280*6,500,450,400,100]';
+	//    c = [350*5,330*3,310*4,280*6,500,450,400,100]';
 	//    // Lower Bound of variable
 	//    lb = repmat(0,8,1);
 	//    // Upper Bound of variables
 	//    ub = [repmat(1,4,1);repmat(%inf,4,1)];
 	//    // Constraint Matrix
-	//    conMatrix = [5,3,4,6,1,1,1,1;
-	//                 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03;
-	//                 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;]
-	//    // Lower Bound of constrains
+	//    A = [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 constraints
 	//    conlb = [ 25; 1.25; 1.25]
-	//    // Upper Bound of constrains
+	//    // Upper Bound of constraints
 	//    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)
+	//    [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,A,conlb,conub,1)
 	//    // Press ENTER to continue 
 	//
 	//    Examples
@@ -86,7 +86,7 @@ function [xopt,fopt,status,output] = symphony (varargin)
 	//    // 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 ..
+	//    c = [   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 ..
@@ -94,57 +94,57 @@ function [xopt,fopt,status,output] = symphony (varargin)
 	//            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)
+	//    A = [ 
+	//        		//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(A,1)
+	//    nbVar = size(A,2)
 	//    // Lower Bound of variables
 	//    lb = repmat(0,nbVar,1)
 	//    // Upper Bound of variables
 	//    ub = repmat(1,nbVar,1)
 	//    // Row Matrix for telling symphony that the is integer or not
 	//    isInt = repmat(%t,1,nbVar)
-	//    // Lower Bound of constrains
+	//    // Lower Bound of constraints
 	//    conLB=repmat(0,nbCon,1);
 	//    // Upper Bound of constraints
 	//    conUB=[11927 13727 11551 13056 13460 ]';
@@ -157,7 +157,7 @@ function [xopt,fopt,status,output] = symphony (varargin)
 	//    // Optimal value
 	//    fopt = [ 24381 ]
 	//    // Calling Symphony
-	//    [x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options);
+	//    [x,f,status,output] = symphony(nbVar,nbCon,c,isInt,lb,ub,A,conLB,conUB,-1,options);
 	// Authors
 	// Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
     
@@ -170,15 +170,26 @@ function [xopt,fopt,status,output] = symphony (varargin)
     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);
+// Initializing all the variables to empty matrix
+	nbVar = [];
+	nbCon = [];
+	c = [];
+	isInt = [];
+	lb = [];
+	ub = [];
+	A = [];
+	conLB = [];
+	conUB = [];
+
+	nbVar = varargin(1);
+	nbCon = varargin(2);
+	c = varargin(3);
+	isInt = varargin(4);
+	lb = varargin(5);
+	ub = varargin(6);
+	A = varargin(7);
+	conLB = varargin(8);
+	conUB = varargin(9);
    
    if ( rhs<10 ) then
       objSense = 1;
@@ -199,12 +210,12 @@ function [xopt,fopt,status,output] = symphony (varargin)
 	isInt = isInt';
    end
 
-   if (size(LB,2)== [nbVar]) then
-	LB = LB';
+   if (size(lb,2)== [nbVar]) then
+	lb = lb';
    end
 
-   if (size(UB,2)== [nbVar]) then
-	UB = UB';
+   if (size(ub,2)== [nbVar]) then
+	ub = ub';
    end
 
    if (size(conLB,2)== [nbCon]) then
@@ -216,12 +227,12 @@ function [xopt,fopt,status,output] = symphony (varargin)
    end
 
 
-   if (size(objCoef,2)~=1) then
+   if (size(c,2)~=1) then
 	errmsg = msprintf(gettext("%s: Objective Coefficients should be a column matrix"), "Symphony");
 	error(errmsg);
    end
 
-   if (size(objCoef,1)~=nbVar) then
+   if (size(c,1)~=nbVar) then
 	errmsg = msprintf(gettext("%s: Number of variables in Objective Coefficients is not equal to number of variables given"), "Symphony");
 	error(errmsg);
    end
@@ -245,25 +256,25 @@ function [xopt,fopt,status,output] = symphony (varargin)
    end
 
    //Check the row of constraint which should equal to the number of constraints
-   if ( size(conMatrix,1) ~= nbCon) then
+   if ( size(A,1) ~= nbCon) then
       errmsg = msprintf(gettext("%s: The number of rows in constraint should be equal to the number of constraints"), "Symphony");
       error(errmsg);
    end
 
    //Check the column of constraint which should equal to the number of variables
-   if ( size(conMatrix,2) ~= nbVar) then
+   if ( size(A,2) ~= nbVar) then
       errmsg = msprintf(gettext("%s: The number of columns in constraint should 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,1) ~= nbVar) then
+   if ( size(lb,1) ~= 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,1) ~= nbVar) then
+   if ( size(ub,1) ~= nbVar) then
       errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "Symphony");
       error(errmsg);
    end
@@ -285,12 +296,12 @@ function [xopt,fopt,status,output] = symphony (varargin)
       error(errmsg); 
    end
    
-   if (size(LB,1)~=1)& (size(LB,2)~=1) then
+   if (size(lb,1)~=1)& (size(lb,2)~=1) then
       errmsg = msprintf(gettext("%s: Lower Bound should be a vector"), "qpipopt");
       error(errmsg); 
    end
    
-   if (size(UB,1)~=1)& (size(UB,2)~=1) then
+   if (size(ub,1)~=1)& (size(ub,2)~=1) then
       errmsg = msprintf(gettext("%s: Upper Bound should be a vector"), "qpipopt");
       error(errmsg); 
    end
@@ -308,11 +319,11 @@ function [xopt,fopt,status,output] = symphony (varargin)
    end
 
 
-   LB = LB';
-   UB = UB';
+   lb = lb';
+   ub = ub';
    isInt = isInt';
-   objCoef = objCoef';
+   c = c';
 
-   [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options);
+   [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,c,isInt,lb,ub,A,conLB,conUB,objSense,options);
 
 endfunction
diff --git a/macros/symphonymat.bin b/macros/symphonymat.bin
index c6d4fbc..0841d41 100644
--- a/macros/symphonymat.bin
+++ b/macros/symphonymat.bin
diff --git a/macros/symphonymat.sci b/macros/symphonymat.sci
index 9226bd6..2c0c18d 100644
--- a/macros/symphonymat.sci
+++ b/macros/symphonymat.sci
@@ -13,47 +13,47 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
   // Solves a mixed integer linear programming constrained optimization problem in intlinprog format.
   //
   //   Calling Sequence
-  //   xopt = symphonymat(C,intcon,A,b)
-  //   xopt = symphonymat(C,intcon,A,b,Aeq,beq)
-  //   xopt = symphonymat(C,intcon,A,b,Aeq,beq,lb,ub)
-  //   xopt = symphonymat(C,intcon,A,b,Aeq,beq,lb,ub,options)
+  //   xopt = symphonymat(c,intcon,A,b)
+  //   xopt = symphonymat(c,intcon,A,b,Aeq,beq)
+  //   xopt = symphonymat(c,intcon,A,b,Aeq,beq,lb,ub)
+  //   xopt = symphonymat(c,intcon,A,b,Aeq,beq,lb,ub,options)
   //   [xopt,fopt,status,output] = symphonymat( ... )
   //   
   //   Parameters
-  //   f : a vector of double, contains coefficients of the variables in the objective 
+  //   c : a vector of double, 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 double. 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 double. 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 double. 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 double. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N. 
+  //   A : Linear inequality constraint matrix, specified as a matrix of double. A represents the linear coefficients in the constraints A*x ≤ b. A has the size where columns equals to the number of variables.
+  //   b : Linear inequality constraint vector, specified as a vector of double. b represents the constant vector in the constraints A*x ≤ b. b has size equals to the number of rows in A. 
+  //   Aeq : Linear equality constraint matrix, specified as a matrix of double. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has the size where columns equals to the number of variables.
+  //   beq : Linear equality constraint vector, specified as a vector of double. beq represents the constant vector in the constraints Aeq*x = beq. beq has size equals to the number of rows in Aeq. 
   //   lb : Lower bounds, specified as a vector or array of double. lb represents the lower bounds elementwise in lb ≤ x ≤ ub.
   //   ub : Upper bounds, specified as a vector or array of double. ub represents the upper bounds elementwise in lb ≤ x ≤ ub.
   //   options : a list containing the the parameters to be set.
-  //   xopt : a vector of double, the computed solution of the optimization problem
+  //   xopt : a vector of double, the computed solution of the optimization problem.
   //   fopt : a double, the function value at x
-  //   status : status flag from symphony.
-  //   output : The output data structure contains detailed informations about the optimization process. Right now it contains number of iteration.
+  //   status : status flag from symphony. 227 is optimal, 228 is Time limit exceeded, 230 is iteration limit exceeded.
+  //   output : The output data structure contains detailed information about the optimization process. This version only contains number of iterations.
   //   
   //   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 
+  //   find the minimum or maximum of C'⋅x such that 
   //
   //   <latex>
   //    \begin{eqnarray}
   //    &\mbox{min}_{x}
-  //    & C^T*x \\
-  //    & \text{subject to} & A*x \leq b \\
-  //    & & Aeq*x = beq \\
+  //    & C^T⋅x \\
+  //    & \text{subject to} & A⋅x \leq b \\
+  //    & & Aeq⋅x = beq \\
   //    & & lb \leq x \leq ub \\
   //	& & x_i \in \!\, \mathbb{Z}, i \in \!\, I
   //    \end{eqnarray}
   //   </latex>
   //   
-  //   We are calling SYMPHONY written in C by gateway files for the actual computation.
+  //   The routine calls SYMPHONY written in C by gateway files for the actual computation.
   //
   // Examples
   //    // Objective function
-  //    C = [350*5,330*3,310*4,280*6,500,450,400,100]';
+  //    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
@@ -79,7 +79,7 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
   //    // 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)
-  //    C = -1*[   504 803 667 1103 834 585 811 856 690 832 846 813 868 793 ..
+  //    c = -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 ..
@@ -88,47 +88,47 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
   //            1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]';
   //    //Constraint Matrix
   //    A = [   //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 ;
+  //            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,1)
+  //    nbVar = size(c,1)
   //    b=[11927 13727 11551 13056 13460 ];
   //    // Lower Bound of variables
   //    lb = repmat(0,1,nbVar)
@@ -148,7 +148,7 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
   //    // Optimal value
   //    fopt = [ 24381 ]
   //    // Calling Symphony
-  //    [x,f,status,output] = symphonymat(C,intcon,A,b,[],[],lb,ub,options);
+  //    [x,f,status,output] = symphonymat(c,intcon,A,b,[],[],lb,ub,options);
   // Authors
   // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
     
@@ -157,24 +157,33 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
    [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
-   
+	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)
+	c = [];
+	intcon = [];
+	A = [];
+	b = [];
+	Aeq = [];
+	beq = [];
+	lb = [];
+	ub = [];
+	
+	
+	c = varargin(1)
+	intcon = varargin(2)
+	A = varargin(3)
+	b = varargin(4)
 
-   if (size(objCoef,2)~=1) then
+   if (size(c,2)~=1) then
 	errmsg = msprintf(gettext("%s: Objective Coefficients should be a column matrix"), "Symphonymat");
 	error(errmsg);
    end
 
 
-   nbVar = size(objCoef,1);
+   nbVar = size(c,1);
 
    if ( rhs<5 ) then
       Aeq = []
@@ -218,25 +227,25 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
 // Check if the user gives row vector 
 // and Changing it to a column matrix
 
-   if (size(lb,2)== [nbVar]) then
-	lb = lb';
-   end
+	if (size(lb,2)== [nbVar]) then
+		lb = lb';
+	end
 
-   if (size(ub,2)== [nbVar]) then
-	ub = ub';
-   end
+	if (size(ub,2)== [nbVar]) then
+		ub = ub';
+	end
 
-   if (size(b,2)== [nbConInEq]) then
-	b = b';
-   end
+	if (size(b,2)== [nbConInEq]) then
+		b = b';
+	end
 
-   if (size(beq,2)== [nbConEq]) then
-	beq = beq';
-   end
+	if (size(beq,2)== [nbConEq]) then
+		beq = beq';
+	end
 
     for i=1:size(intcon,2)
 		if(intcon(i)>nbVar) then
-			errmsg = msprintf(gettext("%s: The values inside intcon should not exceed total number of variable "), "Symphonymat");
+			errmsg = msprintf(gettext("%s: The values inside intcon should be less than the number of variables"), "Symphonymat");
 			error(errmsg);
 		end
 
@@ -246,35 +255,35 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
 		end
 
 		if(modulo(intcon(i),1)) then
-			errmsg = msprintf(gettext("%s: The values inside intcon should be integer "), "Symphonymat");
+			errmsg = msprintf(gettext("%s: The values inside intcon should be an integer "), "Symphonymat");
 			error(errmsg);
 		end
     end
 
    //Check the size of inequality constraint which should equal to the number of inequality constraints
-   if ( size(A,2) ~= nbVar & size(A,2) ~= 0) then
-	errmsg = msprintf(gettext("%s: The size of inequality constraint is not equal to the number of variables"), "Symphonymat");
-	error(errmsg);
-   end
+	if ( size(A,2) ~= nbVar & size(A,2) ~= 0) then
+		errmsg = msprintf(gettext("%s: The size of inequality constraint is not equal to the number of variables"), "Symphonymat");
+		error(errmsg);
+	end
 
 
    //Check the size of lower bound of inequality constraint which should equal to the number of constraints
-   if ( size(b,1) ~= size(A,1)) then
-      errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraint is not equal to the number of constraint"), "Symphonymat");
-      error(errmsg);
-   end
+	if ( size(b,1) ~= size(A,1)) then
+		errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraint is not equal to the number of constraint"), "Symphonymat");
+		error(errmsg);
+	end
 
    //Check the size of equality constraint which should equal to the number of inequality constraints
-   if ( size(Aeq,2) ~= nbVar & size(Aeq,2) ~= 0) then
-	errmsg = msprintf(gettext("%s: The size of equality constraint is not equal to the number of variables"), "Symphonymat");
-	error(errmsg);
-   end
+	if ( size(Aeq,2) ~= nbVar & size(Aeq,2) ~= 0) then
+		errmsg = msprintf(gettext("%s: The size of equality constraint is not equal to the number of variables"), "Symphonymat");
+		error(errmsg);
+	end
 
    //Check the size of upper bound of equality constraint which should equal to the number of constraints
-   if ( size(beq,1) ~= size(Aeq,1)) then
-	errmsg = msprintf(gettext("%s: The equality constraint upper bound is not equal to the number of equality constraint"), "Symphonymat");
-	error(errmsg);
-   end
+	if ( size(beq,1) ~= size(Aeq,1)) then
+		errmsg = msprintf(gettext("%s: The equality constraint upper bound is not equal to the number of equality constraint"), "Symphonymat");
+		error(errmsg);
+	end
 
    //Check the size of Lower Bound which should equal to the number of variables
    if ( size(lb,1) ~= nbVar) then
@@ -349,9 +358,9 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
     //Changing into row vector
     lb = lb';
     ub = ub';
-    objCoef = objCoef';
+    c = c';
     
 
-   [xopt,fopt,status,iter] = symphony_call(nbVar,nbCon,objCoef,isInt,lb,ub,conMatrix,conLB,conUB,objSense,options);
+   [xopt,fopt,status,iter] = symphony_call(nbVar,nbCon,c,isInt,lb,ub,conMatrix,conLB,conUB,objSense,options);
 
 endfunction