From dae3265eed0395c6e0e655a348ec12f3fb9a912f Mon Sep 17 00:00:00 2001
From: Harpreet
Date: Wed, 18 Nov 2015 00:04:28 +0530
Subject: Back Up Files Deleted
---
macros/README.rst~ | 36 ------
macros/qpipopt.sci~ | 233 -------------------------------------
macros/qpipoptmat.sci~ | 265 ------------------------------------------
macros/setOptions.sci~ | 40 -------
macros/symphony.sci~ | 287 ----------------------------------------------
macros/symphony_call.sci~ | 52 ---------
macros/symphonymat.sci~ | 242 --------------------------------------
7 files changed, 1155 deletions(-)
delete mode 100644 macros/README.rst~
delete mode 100644 macros/qpipopt.sci~
delete mode 100644 macros/qpipoptmat.sci~
delete mode 100644 macros/setOptions.sci~
delete mode 100644 macros/symphony.sci~
delete mode 100644 macros/symphony_call.sci~
delete mode 100644 macros/symphonymat.sci~
(limited to 'macros')
diff --git a/macros/README.rst~ b/macros/README.rst~
deleted file mode 100644
index 5a07f63..0000000
--- a/macros/README.rst~
+++ /dev/null
@@ -1,36 +0,0 @@
-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/qpipopt.sci~ b/macros/qpipopt.sci~
deleted file mode 100644
index 35e604b..0000000
--- a/macros/qpipopt.sci~
+++ /dev/null
@@ -1,233 +0,0 @@
-// 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
- //
- //
- // \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}
- //
- //
- // 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.sci~ b/macros/qpipoptmat.sci~
deleted file mode 100644
index e29da8f..0000000
--- a/macros/qpipoptmat.sci~
+++ /dev/null
@@ -1,265 +0,0 @@
-// 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] = qpipoptmat (varargin)
- // Solves a linear quadratic problem.
- //
- // Calling Sequence
- // x = qpipoptmat(H,f)
- // x = qpipoptmat(H,f,A,b)
- // x = qpipoptmat(H,f,A,b,Aeq,beq)
- // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub)
- // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0)
- // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param)
- // [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... )
- //
- // Parameters
- // H : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.
- // f : a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem
- // A : a m x n matrix of doubles, represents the linear coefficients in the inequality constraints
- // b : a column vector of doubles, represents the linear coefficients in the inequality constraints
- // Aeq : a meq x n matrix of doubles, represents the linear coefficients in the equality constraints
- // beq : a vector of doubles, represents the linear coefficients in the equality constraints
- // LB : a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.
- // UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.
- // 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.
- // 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
- //
- //
- // \begin{eqnarray}
- // &\mbox{min}_{x}
- // & 1/2*x'*H*x + f'*x \\
- // & \text{subject to} & A.x \leq b \\
- // & & Aeq.x \leq beq \\
- // & & lb \leq x \leq ub \\
- // \end{eqnarray}
- //
- //
- // We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by Andreas Wächter and Carl Laird.
- //
- // Examples
- // //Find x in R^6 such that:
- //
- // Aeq= [1,-1,1,0,3,1;
- // -1,0,-3,-4,5,6;
- // 2,5,3,0,1,0];
- // beq=[1; 2; 3];
- // A= [0,1,0,1,2,-1;
- // -1,0,2,1,1,0];
- // b = [-1; 2.5];
- // lb=[-1000; -10000; 0; -1000; -1000; -1000];
- // ub=[10000; 100; 1.5; 100; 100; 1000];
- // x0 = repmat(0,6,1);
- // param = list("MaxIter", 300, "CpuTime", 100);
- // //and minimize 0.5*x'*Q*x + p'*x with
- // f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
- // [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param)
- // clear H f A b Aeq beq lb ub;
- //
- // Examples
- // //Find the value of x that minimize following function
- // // f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2
- // // Subject to:
- // // x1 + x2 ≤ 2
- // // –x1 + 2x2 ≤ 2
- // // 2x1 + x2 ≤ 3
- // // 0 ≤ x1, 0 ≤ x2.
- // H = [1 -1; -1 2];
- // f = [-2; -6];
- // A = [1 1; -1 2; 2 1];
- // b = [2; 2; 3];
- // lb = [0; 0];
- // ub = [%inf; %inf];
- // [xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub)
- //
- // Authors
- // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
-
-
-//To check the number of input and output argument
- [lhs , rhs] = argn();
-
-//To check the number of argument given by user
- if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 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
-
- H = varargin(1);
- f = varargin(2);
- nbVar = size(H,1);
-
-
- if ( rhs<2 ) then
- A = []
- b = []
- else
- A = varargin(3);
- b = varargin(4);
- end
-
- if ( rhs<4 ) then
- Aeq = []
- beq = []
- else
- Aeq = varargin(5);
- beq = varargin(6);
- end
-
- if ( rhs<6 ) then
- LB = repmat(-%inf,nbVar,1);
- UB = repmat(%inf,nbVar,1);
- else
- LB = varargin(7);
- UB = varargin(8);
- end
-
-
- 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"), "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"), "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"), "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"), "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"), "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"), "qpipoptmat");
- error(errmsg);
- end
-
- //Check the size of Upper Bound which should equal to the number of variables
- if ( size(UB,1) ~= nbVar) then
- errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipoptmat");
- error(errmsg);
- end
-
- //Check the size of constraints of Lower Bound which should equal to the number of constraints
- if ( size(b,1) ~= nbConInEq & size(b,1) ~= 0) then
- errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraints is not equal to the number of constraints"), "qpipoptmat");
- error(errmsg);
- end
-
- //Check the size of constraints of Upper Bound which should equal to the number of constraints
- if ( size(beq,1) ~= nbConEq & size(beq,1) ~= 0) then
- errmsg = msprintf(gettext("%s: The Upper Bound of equality constraints is not equal to the number of constraints"), "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,x0,options);
-
- xopt = xopt';
- exitflag = status;
- output = struct("Iterations" , []);
- output.Iterations = iter;
- lambda = struct("lower" , [], ..
- "upper" , [], ..
- "ineqlin" , [], ..
- "eqlin" , []);
-
- lambda.lower = Zl;
- lambda.upper = Zu;
- lambda.eqlin = lmbda(1:nbConEq);
- lambda.ineqlin = lmbda(nbConEq+1:nbCon);
-
-
-endfunction
diff --git a/macros/setOptions.sci~ b/macros/setOptions.sci~
deleted file mode 100644
index ef5c36c..0000000
--- a/macros/setOptions.sci~
+++ /dev/null
@@ -1,40 +0,0 @@
-// 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.sci~ b/macros/symphony.sci~
deleted file mode 100644
index 4b11ae8..0000000
--- a/macros/symphony.sci~
+++ /dev/null
@@ -1,287 +0,0 @@
-// 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 double, number of variables.
- // nbCon : a double, number of constraints.
- // objCoeff : a 1 x n matrix of doubles, where n is number of variables, represents coefficients of the variables in the objective.
- // isInt : a vector of boolean, represents wether a variable is constrained to be an integer.
- // LB : a vector of doubles, represents lower bounds of the variables.
- // UB : a vector of doubles, represents upper bounds of the variables.
- // conMatrix : a matrix of doubles, represents matrix representing the constraint matrix.
- // conLB : a vector of doubles, represents lower bounds of the constraints.
- // conUB : a vector of doubles, represents upper bounds of the constraints
- // objSense : The sense (maximization/minimization) of the objective. Use 1(sym_minimize ) or -1 (sym_maximize) here.
- // options : a a list containing the the parameters to be set.
- // xopt : a vector of doubles, the computed solution of the optimization problem.
- // fopt : a double, the function value at x.
- // status : status flag from symphony.
- // output : The output data structure contains detailed informations about the optimization process.
- //
- // Description
- // Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :
- // find the minimum or maximum of f(x) such that
- //
- //
- // \begin{eqnarray}
- // &\mbox{min}_{x}
- // & f(x) \\
- // & \text{subject to} & conLB \leq C(x) \leq conUB \\
- // & & lb \leq x \leq ub \\
- // \end{eqnarray}
- //
- //
- // We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by Ted Ralphs, Menal Guzelsoy and Ashutosh Mahajan.
- //
- // Examples
- // //A basic case :
- // // Objective function
- // c = [350*5,330*3,310*4,280*6,500,450,400,100]';
- // // Lower Bound of variable
- // lb = repmat(0,8,1);
- // // Upper Bound of variables
- // ub = [repmat(1,4,1);repmat(%inf,4,1)];
- // // Constraint Matrix
- // conMatrix = [5,3,4,6,1,1,1,1;
- // 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03;
- // 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;]
- // // Lower Bound of constrains
- // conlb = [ 25; 1.25; 1.25]
- // // Upper Bound of constrains
- // conub = [ 25; 1.25; 1.25]
- // // Row Matrix for telling symphony that the is integer or not
- // isInt = [repmat(%t,1,4) repmat(%f,1,4)];
- // xopt = [1 1 0 1 7.25 0 0.25 3.5]
- // fopt = [8495]
- // // Calling Symphony
- // [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1)
- //
- // Examples
- // // An advanced case where we set some options in symphony
- // // This problem is taken from
- // // P.C.Chu and J.E.Beasley
- // // "A genetic algorithm for the multidimensional knapsack problem",
- // // Journal of Heuristics, vol. 4, 1998, pp63-86.
- // // The problem to be solved is:
- // // Max sum{j=1,...,n} p(j)x(j)
- // // st sum{j=1,...,n} r(i,j)x(j) <= b(i) i=1,...,m
- // // x(j)=0 or 1
- // // The function to be maximize i.e. P(j)
- // p = [ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 ..
- // 825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 ..
- // 877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 ..
- // 957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 ..
- // 959 668 507 855 986 831 821 825 868 852 832 828 799 686 ..
- // 510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 ..
- // 1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]';
- // //Constraint Matrix
- // conMatrix = [
- // //Constraint 1
- // 42 41 523 215 819 551 69 193 582 375 367 478 162 898 ..
- // 550 553 298 577 493 183 260 224 852 394 958 282 402 604 ..
- // 164 308 218 61 273 772 191 117 276 877 415 873 902 465 ..
- // 320 870 244 781 86 622 665 155 680 101 665 227 597 354 ..
- // 597 79 162 998 849 136 112 751 735 884 71 449 266 420 ..
- // 797 945 746 46 44 545 882 72 383 714 987 183 731 301 ..
- // 718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298;
- // //Constraint 2
- // 509 883 229 569 706 639 114 727 491 481 681 948 687 941 ..
- // 350 253 573 40 124 384 660 951 739 329 146 593 658 816 ..
- // 638 717 779 289 430 851 937 289 159 260 930 248 656 833 ..
- // 892 60 278 741 297 967 86 249 354 614 836 290 893 857 ..
- // 158 869 206 504 799 758 431 580 780 788 583 641 32 653 ..
- // 252 709 129 368 440 314 287 854 460 594 512 239 719 751 ..
- // 708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850;
- // //Constraint 3
- // 806 361 199 781 596 669 957 358 259 888 319 751 275 177 ..
- // 883 749 229 265 282 694 819 77 190 551 140 442 867 283 ..
- // 137 359 445 58 440 192 485 744 844 969 50 833 57 877 ..
- // 482 732 968 113 486 710 439 747 174 260 877 474 841 422 ..
- // 280 684 330 910 791 322 404 403 519 148 948 414 894 147 ..
- // 73 297 97 651 380 67 582 973 143 732 624 518 847 113 ..
- // 382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ;
- // //Constraint 4
- // 404 197 817 1000 44 307 39 659 46 334 448 599 931 776 ..
- // 263 980 807 378 278 841 700 210 542 636 388 129 203 110 ..
- // 817 502 657 804 662 989 585 645 113 436 610 948 919 115 ..
- // 967 13 445 449 740 592 327 167 368 335 179 909 825 614 ..
- // 987 350 179 415 821 525 774 283 427 275 659 392 73 896 ..
- // 68 982 697 421 246 672 649 731 191 514 983 886 95 846 ..
- // 689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322;
- // //Constrain 5
- // 475 36 287 577 45 700 803 654 196 844 657 387 518 143 ..
- // 515 335 942 701 332 803 265 922 908 139 995 845 487 100 ..
- // 447 653 649 738 424 475 425 926 795 47 136 801 904 740 ..
- // 768 460 76 660 500 915 897 25 716 557 72 696 653 933 ..
- // 420 582 810 861 758 647 237 631 271 91 75 756 409 440 ..
- // 483 336 765 637 981 980 202 35 594 689 602 76 767 693 ..
- // 893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ;
- // ];
- // nbCon = size(conMatrix,1)
- // nbVar = size(conMatrix,2)
- // // Lower Bound of variables
- // lb = repmat(0,nbVar,1)
- // // Upper Bound of variables
- // ub = repmat(1,nbVar,1)
- // // Row Matrix for telling symphony that the is integer or not
- // isInt = repmat(%t,1,nbVar)
- // // Lower Bound of constrains
- // conLB=repmat(0,nbCon,1);
- // // Upper Bound of constraints
- // conUB=[11927 13727 11551 13056 13460 ]';
- // options = list("time_limit", 25);
- // // The expected solution :
- // // Output variables
- // xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 ..
- // 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 1 0 ..
- // 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0]
- // // Optimal value
- // fopt = [ 24381 ]
- // // Calling Symphony
- // [x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options)
- //
- // Authors
- // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
-
-//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|size(varargin(11))==0) then
- options = list();
- else
- options = varargin(11);
- end
-
-// Check if the user gives row vector
-// and Changing it to a column matrix
-
- if (size(isInt,2)== [nbVar]) then
- isInt = isInt';
- end
-
- if (size(LB,2)== [nbVar]) then
- LB = LB';
- end
-
- if (size(UB,2)== [nbVar]) then
- UB = UB';
- end
-
- if (size(conLB,2)== [nbVar]) then
- conLB = conLB';
- end
-
- if (size(conUB,2)== [nbVar]) then
- conUB = conUB';
- end
-
-
- if (size(objCoef,2)~=1) then
- errmsg = msprintf(gettext("%s: Objective Coefficients should be a column matrix"), "Symphony");
- error(errmsg);
- end
-
- if (size(objCoef,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
-
- //Check the size of isInt which should equal to the number of variables
- if(size(isInt,1)~=nbVar) then
- errmsg = msprintf(gettext("%s: The size of isInt is not equal to the number of variables"), "Symphony");
- error(errmsg);
- end
-
- //Check the size of lower bound of inequality constraint which should equal to the number of constraints
- if ( size(conLB,1) ~= nbCon) then
- errmsg = msprintf(gettext("%s: The Lower Bound of constraint is not equal to the number of constraint"), "Symphony");
- error(errmsg);
- end
-
- //Check the size of lower bound of inequality constraint which should equal to the number of constraints
- if ( size(conUB,1) ~= nbCon) then
- errmsg = msprintf(gettext("%s: The Upper Bound of constraint is not equal to the number of constraint"), "Symphony");
- error(errmsg);
- end
-
- //Check the row of constraint which should equal to the number of constraints
- if ( size(conMatrix,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
- 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
- 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
- errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "Symphony");
- error(errmsg);
- end
-
- if (type(options) ~= 15) then
- errmsg = msprintf(gettext("%s: Options should be a list "), "Symphony");
- error(errmsg);
- end
-
- if (modulo(size(options),2)) then
- errmsg = msprintf(gettext("%s: Size of parameters should be even"), "Symphony");
- error(errmsg);
- end
-
- LB = LB';
- UB = UB';
- isInt = isInt';
- objCoef = objCoef';
-
- [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options);
-
-endfunction
diff --git a/macros/symphony_call.sci~ b/macros/symphony_call.sci~
deleted file mode 100644
index 057ba63..0000000
--- a/macros/symphony_call.sci~
+++ /dev/null
@@ -1,52 +0,0 @@
-// 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.sci~ b/macros/symphonymat.sci~
deleted file mode 100644
index 455dd67..0000000
--- a/macros/symphonymat.sci~
+++ /dev/null
@@ -1,242 +0,0 @@
-// 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
- //
- //
- // \begin{eqnarray}
- // &\mbox{min}_{x}
- // & f(x) \\
- // & \text{subject to} & conLB \leq C(x) \leq conUB \\
- // & & lb \leq x \leq ub \\
- // \end{eqnarray}
- //
- //
- // 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