diff options
Diffstat (limited to 'macros')
| -rw-r--r-- | macros/README.rst | 36 | ||||
| -rw-r--r-- | macros/README.rst~ | 36 | ||||
| -rw-r--r-- | macros/lib | bin | 480 -> 480 bytes | |||
| -rw-r--r-- | macros/names | 2 | ||||
| -rw-r--r-- | macros/qpipopt.bin | bin | 29496 -> 33680 bytes | |||
| -rw-r--r-- | macros/qpipopt.sci | 54 | ||||
| -rw-r--r-- | macros/qpipopt.sci~ | 233 | ||||
| -rw-r--r-- | macros/qpipoptmat.bin | bin | 31280 -> 38128 bytes | |||
| -rw-r--r-- | macros/qpipoptmat.sci | 74 | ||||
| -rw-r--r-- | macros/qpipoptmat.sci~ | 101 | ||||
| -rw-r--r-- | macros/setOptions.bin | bin | 3164 -> 3040 bytes | |||
| -rw-r--r-- | macros/setOptions.sci | 17 | ||||
| -rw-r--r-- | macros/setOptions.sci~ | 40 | ||||
| -rw-r--r-- | macros/symphony.bin | bin | 43716 -> 43868 bytes | |||
| -rw-r--r-- | macros/symphony.sci | 10 | ||||
| -rw-r--r-- | macros/symphony.sci~ | 227 | ||||
| -rw-r--r-- | macros/symphony_call.bin | bin | 3932 -> 4064 bytes | |||
| -rw-r--r-- | macros/symphony_call.sci | 4 | ||||
| -rw-r--r-- | macros/symphony_call.sci~ | 52 | ||||
| -rw-r--r-- | macros/symphonymat.bin | bin | 0 -> 45960 bytes | |||
| -rw-r--r-- | macros/symphonymat.sci | 242 | ||||
| -rw-r--r-- | macros/symphonymat.sci~ | 242 |
22 files changed, 1307 insertions, 63 deletions
diff --git a/macros/README.rst b/macros/README.rst new file mode 100644 index 0000000..5a07f63 --- /dev/null +++ b/macros/README.rst @@ -0,0 +1,36 @@ +MACROS +====== + +These files mainly consist of functions for checking the input and calling the gateway functions + +symphony +-------- + +It takes the input in symphony style and checks the input. After all the checks call the symphony_call function. + +symphonymat +----------- + +It takes the input in symphony style and checks the input. After all the checks call the symphony_call function. + +symphony_call +------------- + +It calls the gateway functions to initialize, set options and to solve it. After that it will call the functions to get the solution for the problem. + +setOptions +---------- + +It will set the options in the symphony. + +qpipopt +------- + +It synatize the input and call solveqp in the ipopt style. + +qpipopt +------- + +It synatize the input and call solveqp in the quadprog style. + + diff --git a/macros/README.rst~ b/macros/README.rst~ new file mode 100644 index 0000000..5a07f63 --- /dev/null +++ b/macros/README.rst~ @@ -0,0 +1,36 @@ +MACROS +====== + +These files mainly consist of functions for checking the input and calling the gateway functions + +symphony +-------- + +It takes the input in symphony style and checks the input. After all the checks call the symphony_call function. + +symphonymat +----------- + +It takes the input in symphony style and checks the input. After all the checks call the symphony_call function. + +symphony_call +------------- + +It calls the gateway functions to initialize, set options and to solve it. After that it will call the functions to get the solution for the problem. + +setOptions +---------- + +It will set the options in the symphony. + +qpipopt +------- + +It synatize the input and call solveqp in the ipopt style. + +qpipopt +------- + +It synatize the input and call solveqp in the quadprog style. + + Binary files differdiff --git a/macros/names b/macros/names index 40e5934..e068c5a 100644 --- a/macros/names +++ b/macros/names @@ -3,4 +3,4 @@ qpipoptmat setOptions symphony symphony_call -symphony_mat +symphonymat diff --git a/macros/qpipopt.bin b/macros/qpipopt.bin Binary files differindex 0cdc0d9..07db2ad 100644 --- a/macros/qpipopt.bin +++ b/macros/qpipopt.bin diff --git a/macros/qpipopt.sci b/macros/qpipopt.sci index efcca01..8f3945e 100644 --- a/macros/qpipopt.sci +++ b/macros/qpipopt.sci @@ -16,16 +16,13 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) // Calling Sequence // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0) + // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0,param) // [xopt,fopt,exitflag,output,lamda] = qpipopt( ... ) // // Parameters // nbVar : a 1 x 1 matrix of doubles, number of variables // nbCon : a 1 x 1 matrix of doubles, number of constraints -<<<<<<< HEAD // Q : a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. -======= - // Q : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. ->>>>>>> c2679735a3443017e003ca095d0476bae2dd8e40 // p : a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem // LB : a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables. // UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables. @@ -33,6 +30,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) // conLB : a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints. // conUB : a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints. // x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables. + // param : a list containing the the parameters to be set. // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem. // fopt : a 1x1 matrix of doubles, the function value at x. // exitflag : Integer identifying the reason the algorithm terminated. @@ -69,7 +67,9 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) // p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6); // nbVar = 6; // nbCon = 5; - // [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) + // x0 = repmat(0,nbVar,1); + // param = list("MaxIter", 300, "CpuTime", 100); + // [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param) // // Examples // //Find the value of x that minimize following function @@ -98,8 +98,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) [lhs , rhs] = argn(); //To check the number of argument given by user - if ( rhs < 9 | rhs > 10 ) then - errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9 or 10"), "qpipopt", rhs); + if ( rhs < 9 | rhs > 11 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9, 10 or 11"), "qpipopt", rhs); error(errmsg) end @@ -113,22 +113,53 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) conMatrix = varargin(7); conLB = varargin(8); conUB = varargin(9); + - if ( rhs<10 ) then - x0 = repmat(0,1,nbVar) + if ( rhs<10 | size(varargin(10)) ==0 ) then + x0 = repmat(0,nbVar,1); else x0 = varargin(10); end + if ( rhs<11 ) then + param = list(); + else + param =varargin(11); + end + + if (modulo(size(param),2)) then + errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipopt"); + error(errmsg); + end + + + options = list(.. + "MaxIter" , [3000], ... + "CpuTime" , [600] ... + ); + + for i = 1:(size(param))/2 + select param(2*i-1) + case "MaxIter" then + options(2*i) = param(2*i); + case "CpuTime" then + options(2*i) = param(2*i); + else + errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipopt", param(2*i-1)); + error(errmsg) + end + end + //IPOpt wants it in row matrix form p = p'; LB = LB'; UB = UB'; conLB = conLB'; conUB = conUB'; + x0 = x0'; //Checking the Q matrix which needs to be a symmetric matrix - if ( Q~=Q') then + if ( ~isequal(Q,Q') ) then errmsg = msprintf(gettext("%s: Q is not a symmetric matrix"), "qpipopt"); error(errmsg); end @@ -182,7 +213,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) error(errmsg); end - [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0); + + [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options); xopt = xopt'; exitflag = status; diff --git a/macros/qpipopt.sci~ b/macros/qpipopt.sci~ new file mode 100644 index 0000000..35e604b --- /dev/null +++ b/macros/qpipopt.sci~ @@ -0,0 +1,233 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + + +function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) + // Solves a linear quadratic problem. + // + // Calling Sequence + // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) + // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0) + // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0,param) + // [xopt,fopt,exitflag,output,lamda] = qpipopt( ... ) + // + // Parameters + // nbVar : a 1 x 1 matrix of doubles, number of variables + // nbCon : a 1 x 1 matrix of doubles, number of constraints + // Q : a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. + // p : a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem + // LB : a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables. + // UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables. + // conMatrix : a m x n matrix of doubles, where n is number of variables and m is number of constraints, contains matrix representing the constraint matrix + // conLB : a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints. + // conUB : a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints. + // x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables. + // param : a list containing the the parameters to be set. + // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem. + // fopt : a 1x1 matrix of doubles, the function value at x. + // exitflag : Integer identifying the reason the algorithm terminated. + // output : Structure containing information about the optimization. + // lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type). + // + // Description + // Search the minimum of a constrained linear quadratic optimization problem specified by : + // find the minimum of f(x) such that + // + // <latex> + // \begin{eqnarray} + // &\mbox{min}_{x} + // & 1/2*x'*Q*x + p'*x \\ + // & \text{subject to} & conLB \leq C(x) \leq conUB \\ + // & & lb \leq x \leq ub \\ + // \end{eqnarray} + // </latex> + // + // We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by Andreas Wächter and Carl Laird. + // + // Examples + // //Find x in R^6 such that: + // conMatrix= [1,-1,1,0,3,1; + // -1,0,-3,-4,5,6; + // 2,5,3,0,1,0 + // 0,1,0,1,2,-1; + // -1,0,2,1,1,0]; + // conLB=[1;2;3;-%inf;-%inf]; + // conUB = [1;2;3;-1;2.5]; + // lb=[-1000;-10000; 0; -1000; -1000; -1000]; + // ub=[10000; 100; 1.5; 100; 100; 1000]; + // //and minimize 0.5*x'*Q*x + p'*x with + // p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6); + // nbVar = 6; + // nbCon = 5; + // x0 = repmat(0,nbVar,1); + // param = list("MaxIter", 300, "CpuTime", 100); + // [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param) + // + // Examples + // //Find the value of x that minimize following function + // // f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 + // // Subject to: + // // x1 + x2 ≤ 2 + // // –x1 + 2x2 ≤ 2 + // // 2x1 + x2 ≤ 3 + // // 0 ≤ x1, 0 ≤ x2. + // Q = [1 -1; -1 2]; + // p = [-2; -6]; + // conMatrix = [1 1; -1 2; 2 1]; + // conUB = [2; 2; 3]; + // conLB = [-%inf; -%inf; -%inf]; + // lb = [0; 0]; + // ub = [%inf; %inf]; + // nbVar = 2; + // nbCon = 3; + // [xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) + // + // Authors + // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + + +//To check the number of input and output argument + [lhs , rhs] = argn(); + +//To check the number of argument given by user + if ( rhs < 9 | rhs > 11 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9, 10 or 11"), "qpipopt", rhs); + error(errmsg) + end + + + nbVar = varargin(1); + nbCon = varargin(2); + Q = varargin(3); + p = varargin(4); + LB = varargin(5); + UB = varargin(6); + conMatrix = varargin(7); + conLB = varargin(8); + conUB = varargin(9); + + + if ( rhs<10 | size(varargin(10)) ==0 ) then + x0 = repmat(0,nbVar,1); + else + x0 = varargin(10); + end + + if ( rhs<11 ) then + param = []; + else + param =varargin(11); + end + + if (modulo(size(param),2)) then + errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipopt"); + error(errmsg); + end + + + options = list(.. + "MaxIter" , [3000], ... + "CpuTime" , [600] ... + ); + + for i = 1:(size(param))/2 + + select param(2*i-1) + case "MaxIter" then + options(1) = param(2*i); + case "CpuTime" then + options(3) = param(2*i); + else + errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipopt", param(2*i-1)); + error(errmsg) + end + end + + //IPOpt wants it in row matrix form + p = p'; + LB = LB'; + UB = UB'; + conLB = conLB'; + conUB = conUB'; + x0 = x0'; + + //Checking the Q matrix which needs to be a symmetric matrix + if ( ~isequal(Q,Q') ) then + errmsg = msprintf(gettext("%s: Q is not a symmetric matrix"), "qpipopt"); + error(errmsg); + end + + //Check the size of Q which should equal to the number of variable + if ( size(Q) ~= [nbVar nbVar]) then + errmsg = msprintf(gettext("%s: The Size of Q is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + //Check the size of p which should equal to the number of variable + if ( size(p,2) ~= [nbVar]) then + errmsg = msprintf(gettext("%s: The Size of p is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + + //Check the size of constraint which should equal to the number of variables + if ( size(conMatrix,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The size of constraints is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + //Check the size of Lower Bound which should equal to the number of variables + if ( size(LB,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + //Check the size of Upper Bound which should equal to the number of variables + if ( size(UB,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + //Check the size of constraints of Lower Bound which should equal to the number of constraints + if ( size(conLB,2) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Lower Bound of constraints is not equal to the number of constraints"), "qpipopt"); + error(errmsg); + end + + //Check the size of constraints of Upper Bound which should equal to the number of constraints + if ( size(conUB,2) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Upper Bound of constraints is not equal to the number of constraints"), "qpipopt"); + error(errmsg); + end + + //Check the size of initial of variables which should equal to the number of variables + if ( size(x0,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The initial guess of variables is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + + [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options); + + xopt = xopt'; + exitflag = status; + output = struct("Iterations" , []); + output.Iterations = iter; + lambda = struct("lower" , [], .. + "upper" , [], .. + "constraint" , []); + + lambda.lower = Zl; + lambda.upper = Zu; + lambda.constraint = lmbda; + + +endfunction diff --git a/macros/qpipoptmat.bin b/macros/qpipoptmat.bin Binary files differindex 68c3988..668402c 100644 --- a/macros/qpipoptmat.bin +++ b/macros/qpipoptmat.bin diff --git a/macros/qpipoptmat.sci b/macros/qpipoptmat.sci index 2f3e911..6ae20c0 100644 --- a/macros/qpipoptmat.sci +++ b/macros/qpipoptmat.sci @@ -14,11 +14,12 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) // Solves a linear quadratic problem. // // Calling Sequence - // xopt = qpipoptmat(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) // x = qpipoptmat(H,f) // x = qpipoptmat(H,f,A,b) // x = qpipoptmat(H,f,A,b,Aeq,beq) // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub) + // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0) + // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param) // [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... ) // // Parameters @@ -30,6 +31,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) // beq : a vector of doubles, represents the linear coefficients in the equality constraints // LB : a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables. // UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables. + // x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables. + // param : a list containing the the parameters to be set. // xopt : a nx1 matrix of doubles, the computed solution of the optimization problem. // fopt : a 1x1 matrix of doubles, the function value at x. // exitflag : Integer identifying the reason the algorithm terminated. @@ -64,9 +67,11 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) // b = [-1; 2.5]; // lb=[-1000; -10000; 0; -1000; -1000; -1000]; // ub=[10000; 100; 1.5; 100; 100; 1000]; + // x0 = repmat(0,6,1); + // param = list("MaxIter", 300, "CpuTime", 100); // //and minimize 0.5*x'*Q*x + p'*x with // f=[1; 2; 3; 4; 5; 6]; H=eye(6,6); - // [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub) + // [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param) // clear H f A b Aeq beq lb ub; // // Examples @@ -93,8 +98,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) [lhs , rhs] = argn(); //To check the number of argument given by user - if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 8 ) then - errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8]"), "qpipopt", rhs); + if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 10 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8 9 10]"), "qpipoptmat", rhs); error(errmsg) end @@ -126,7 +131,50 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) LB = varargin(7); UB = varargin(8); end - + + + if ( rhs<9 | size(varargin(9)) ==0 ) then + x0 = repmat(0,nbVar,1) + else + x0 = varargin(9); + end + + if ( rhs<10 ) then + param = list(); + else + param =varargin(10); + end + + + if (modulo(size(param),2)) then + errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipoptmat"); + error(errmsg); + end + + if (modulo(size(param),2)) then + errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipoptmat"); + error(errmsg); + end + + + options = list(.. + "MaxIter" , [3000], ... + "CpuTime" , [600] ... + ); + + for i = 1:(size(param))/2 + + select param(2*i-1) + case "MaxIter" then + options(2*i-1) = param(2*i); + case "CpuTime" then + options(2*i-1) = param(2*i); + else + errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipoptmat", param(2*i-1)); + error(errmsg) + end + end + nbConInEq = size(A,1); nbConEq = size(Aeq,1); @@ -168,33 +216,41 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) error(errmsg); end -//Check the size of Upper Bound which should equal to the number of variables + //Check the size of Upper Bound which should equal to the number of variables if ( size(UB,1) ~= nbVar) then errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end -//Check the size of constraints of Lower Bound which should equal to the number of constraints + //Check the size of constraints of Lower Bound which should equal to the number of constraints if ( size(b,1) ~= nbConInEq & size(b,1) ~= 0) then errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraints is not equal to the number of constraints"), "qpipoptmat"); error(errmsg); end -//Check the size of constraints of Upper Bound which should equal to the number of constraints + //Check the size of constraints of Upper Bound which should equal to the number of constraints if ( size(beq,1) ~= nbConEq & size(beq,1) ~= 0) then errmsg = msprintf(gettext("%s: The Upper Bound of equality constraints is not equal to the number of constraints"), "qpipoptmat"); error(errmsg); end + + //Check the size of initial of variables which should equal to the number of variables + if ( size(x0,1) ~= nbVar) then + errmsg = msprintf(gettext("%s: The initial guess of variables is not equal to the number of variables"), "qpipoptmat"); + error(errmsg); + end + //Converting it into ipopt format f = f'; LB = LB'; UB = UB'; + x0 = x0'; conMatrix = [Aeq;A]; nbCon = size(conMatrix,1); conLB = [beq; repmat(-%inf,nbConInEq,1)]'; conUB = [beq;b]' ; - [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB); + [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB,x0,options); xopt = xopt'; exitflag = status; diff --git a/macros/qpipoptmat.sci~ b/macros/qpipoptmat.sci~ index 4c72216..e29da8f 100644 --- a/macros/qpipoptmat.sci~ +++ b/macros/qpipoptmat.sci~ @@ -10,16 +10,17 @@ // http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt -function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) +function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) // Solves a linear quadratic problem. // // Calling Sequence - // xopt = qpipopt_mat(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) - // x = qpipopt_mat(H,f) - // x = qpipopt_mat(H,f,A,b) - // x = qpipopt_mat(H,f,A,b,Aeq,beq) - // x = qpipopt_mat(H,f,A,b,Aeq,beq,lb,ub) - // [xopt,fopt,exitflag,output,lamda] = qpipopt_mat( ... ) + // x = qpipoptmat(H,f) + // x = qpipoptmat(H,f,A,b) + // x = qpipoptmat(H,f,A,b,Aeq,beq) + // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub) + // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0) + // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param) + // [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... ) // // Parameters // H : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. @@ -30,6 +31,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) // beq : a vector of doubles, represents the linear coefficients in the equality constraints // LB : a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables. // UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables. + // x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables. + // param : a list containing the the parameters to be set. // xopt : a nx1 matrix of doubles, the computed solution of the optimization problem. // fopt : a 1x1 matrix of doubles, the function value at x. // exitflag : Integer identifying the reason the algorithm terminated. @@ -64,9 +67,11 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) // b = [-1; 2.5]; // lb=[-1000; -10000; 0; -1000; -1000; -1000]; // ub=[10000; 100; 1.5; 100; 100; 1000]; + // x0 = repmat(0,6,1); + // param = list("MaxIter", 300, "CpuTime", 100); // //and minimize 0.5*x'*Q*x + p'*x with // f=[1; 2; 3; 4; 5; 6]; H=eye(6,6); - // [xopt,fopt,exitflag,output,lambda]=qpipopt_mat(H,f,A,b,Aeq,beq,lb,ub) + // [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param) // clear H f A b Aeq beq lb ub; // // Examples @@ -83,7 +88,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) // b = [2; 2; 3]; // lb = [0; 0]; // ub = [%inf; %inf]; - // [xopt,fopt,exitflag,output,lambda] = qpipopt_mat(H,f,A,b,[],[],lb,ub) + // [xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub) // // Authors // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh @@ -93,8 +98,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) [lhs , rhs] = argn(); //To check the number of argument given by user - if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 8 ) then - errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8]"), "qpipopt", rhs); + if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 10 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8 9 10]"), "qpipoptmat", rhs); error(errmsg) end @@ -126,75 +131,121 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) LB = varargin(7); UB = varargin(8); end - + + + if ( rhs<10 | size(varargin(9)) ==0 ) then + x0 = repmat(0,nbVar,1) + else + x0 = varargin(9); + end + + if ( rhs<11 ) then + param = list(); + else + param =varargin(10); + end + + + if (modulo(size(param),2)) then + errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipoptmat"); + error(errmsg); + end + + + options = list(.. + "MaxIter" , [3000], ... + "CpuTime" , [600] ... + ); + + for i = 1:(size(param))/2 + + select param(2*i-1) + case "MaxIter" then + options(2*i-1) = param(2*i); + case "CpuTime" then + options(2*i-1) = param(2*i); + else + errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipoptmat", param(2*i-1)); + error(errmsg) + end + end + nbConInEq = size(A,1); nbConEq = size(Aeq,1); //Checking the H matrix which needs to be a symmetric matrix if ( H~=H') then - errmsg = msprintf(gettext("%s: H is not a symmetric matrix"), "qpipopt_mat"); + errmsg = msprintf(gettext("%s: H is not a symmetric matrix"), "qpipoptmat"); error(errmsg); end //Check the size of H which should equal to the number of variable if ( size(H) ~= [nbVar nbVar]) then - errmsg = msprintf(gettext("%s: The Size of H is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The Size of H is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end //Check the size of f which should equal to the number of variable if ( size(f,1) ~= [nbVar]) then - errmsg = msprintf(gettext("%s: The Size of f is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The Size of f is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end //Check the size of inequality constraint which should be equal to the number of variables if ( size(A,2) ~= nbVar & size(A,2) ~= 0) then - errmsg = msprintf(gettext("%s: The size of inequality constraints is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The size of inequality constraints is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end //Check the size of equality constraint which should be equal to the number of variables if ( size(Aeq,2) ~= nbVar & size(Aeq,2) ~= 0 ) then - errmsg = msprintf(gettext("%s: The size of equality constraints is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The size of equality constraints is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end //Check the size of Lower Bound which should be equal to the number of variables if ( size(LB,1) ~= nbVar) then - errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end -//Check the size of Upper Bound which should equal to the number of variables + //Check the size of Upper Bound which should equal to the number of variables if ( size(UB,1) ~= nbVar) then - errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end -//Check the size of constraints of Lower Bound which should equal to the number of constraints + //Check the size of constraints of Lower Bound which should equal to the number of constraints if ( size(b,1) ~= nbConInEq & size(b,1) ~= 0) then - errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraints is not equal to the number of constraints"), "qpipopt"); + errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraints is not equal to the number of constraints"), "qpipoptmat"); error(errmsg); end -//Check the size of constraints of Upper Bound which should equal to the number of constraints + //Check the size of constraints of Upper Bound which should equal to the number of constraints if ( size(beq,1) ~= nbConEq & size(beq,1) ~= 0) then - errmsg = msprintf(gettext("%s: The Upper Bound of equality constraints is not equal to the number of constraints"), "qp_ipopt"); + errmsg = msprintf(gettext("%s: The Upper Bound of equality constraints is not equal to the number of constraints"), "qpipoptmat"); error(errmsg); end + + //Check the size of initial of variables which should equal to the number of variables + if ( size(x0,1) ~= nbVar) then + errmsg = msprintf(gettext("%s: The initial guess of variables is not equal to the number of variables"), "qpipoptmat"); + error(errmsg); + end + //Converting it into ipopt format f = f'; LB = LB'; UB = UB'; + x0 = x0'; conMatrix = [Aeq;A]; nbCon = size(conMatrix,1); conLB = [beq; repmat(-%inf,nbConInEq,1)]'; conUB = [beq;b]' ; - [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB); + [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB,x0,options); xopt = xopt'; exitflag = status; diff --git a/macros/setOptions.bin b/macros/setOptions.bin Binary files differindex c5a69df..8d23e73 100644 --- a/macros/setOptions.bin +++ b/macros/setOptions.bin diff --git a/macros/setOptions.sci b/macros/setOptions.sci index 138e577..68aad02 100644 --- a/macros/setOptions.sci +++ b/macros/setOptions.sci @@ -12,9 +12,8 @@ function setOptions(varargin) options = varargin(1); - nbOpt = size(options,2); + nbOpt = size(options); - value = strtod(options) if (nbOpt~=0) then for i = 1:(nbOpt/2) @@ -22,21 +21,19 @@ function setOptions(varargin) //Setting the parameters //Check if the given parameter is String - if (value(2*i) == %nan ) then - sym_setStrParam(options(2*i - 1),value(2*i)); + if (type(options(2*i)) == 10 ) then + sym_setStrParam(options(2*i - 1),options(2*i)); //Check if the given parameter is Double - elseif(type(value(2*i))==1) then - sym_setDblParam(options(2*i - 1),value(2*i)); + elseif(type(options(2*i))==1) then + sym_setDblParam(options(2*i - 1),options(2*i)); //Check if the given parameter is Integer - elseif(type(value(2*i))==8) + elseif(type(options(2*i))==8) sym_setIntParam(options(2*i - 1),options(2*i)); end - - end + end end - endfunction diff --git a/macros/setOptions.sci~ b/macros/setOptions.sci~ new file mode 100644 index 0000000..ef5c36c --- /dev/null +++ b/macros/setOptions.sci~ @@ -0,0 +1,40 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +function setOptions(varargin) + + options = varargin(1); + nbOpt = size(options); + + + if (nbOpt~=0) then + for i = 1:(nbOpt/2) + + //Setting the parameters + + //Check if the given parameter is String + if (type(options(2*i)) == 10 ) then + sym_setStrParam(options(2*i - 1),options(2*i)); + + //Check if the given parameter is Double + elseif(type(options(2*i))==1) then + sym_setDblParam(options(2*i - 1),options(2*i)); + + //Check if the given parameter is Integer + elseif(type(options(2*i))==8) + sym_setIntParam(options(2*i - 1),options(2*i)); + end + + end + end + +endfunction + diff --git a/macros/symphony.bin b/macros/symphony.bin Binary files differindex ae6c958..d2aa822 100644 --- a/macros/symphony.bin +++ b/macros/symphony.bin diff --git a/macros/symphony.sci b/macros/symphony.sci index f221160..9677720 100644 --- a/macros/symphony.sci +++ b/macros/symphony.sci @@ -71,7 +71,8 @@ function [xopt,fopt,status,output] = symphony (varargin) // xopt = [1 1 0 1 7.25 0 0.25 3.5] // fopt = [8495] // // Calling Symphony - // [x,f,iter] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1); + // [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1) + // // Examples // // An advanced case where we set some options in symphony // // This problem is taken from @@ -145,7 +146,7 @@ function [xopt,fopt,status,output] = symphony (varargin) // conLB=repmat(0,nbCon,1); // // Upper Bound of constraints // conUB=[11927 13727 11551 13056 13460 ]'; - // options = ["time_limit" "25"] + // options = list("time_limit", 25); // // The expected solution : // // Output variables // xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. @@ -154,7 +155,7 @@ function [xopt,fopt,status,output] = symphony (varargin) // // Optimal value // fopt = [ 24381 ] // // Calling Symphony - // [x,f,iter]= symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options) + // [x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options) // // Authors // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh @@ -185,7 +186,7 @@ function [xopt,fopt,status,output] = symphony (varargin) end if (rhs<11) then - options = []; + options = list(); else options = varargin(11); end @@ -224,4 +225,3 @@ function [xopt,fopt,status,output] = symphony (varargin) [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options); endfunction - diff --git a/macros/symphony.sci~ b/macros/symphony.sci~ new file mode 100644 index 0000000..d5c8e44 --- /dev/null +++ b/macros/symphony.sci~ @@ -0,0 +1,227 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +function [xopt,fopt,status,output] = symphony (varargin) + // Solves a mixed integer linear programming constrained optimization problem. + // + // Calling Sequence + // xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB) + // xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense) + // xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options) + // [xopt,fopt,status,output] = symphony( ... ) + // + // Parameters + // nbVar : a 1 x 1 matrix of doubles, number of variables + // nbCon : a 1 x 1 matrix of doubles, number of constraints + // objCoeff : a 1 x n matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective + // isInt : a 1 x n matrix of boolean, where n is number of variables, representing wether a variable is constrained to be an integer + // LB : a 1 x n matrix of doubles, where n is number of variables, contains lower bounds of the variables. Bound can be negative infinity + // UB : a 1 x n matrix of doubles, where n is number of variables, contains upper bounds of the variables. Bound can be infinity + // conMatrix : a m x n matrix of doubles, where n is number of variables and m is number of constraints, contains matrix representing the constraint matrix + // conLB : a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints. + // conUB : a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints + // objSense : The sense (maximization/minimization) of the objective. Use 1(sym_minimize ) or -1 (sym_maximize) here + // options : a 1xq marix of string, provided to set the paramters in symphony + // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem + // fopt : a 1x1 matrix of doubles, the function value at x + // status : status flag from symphony + // output : The output data structure contains detailed informations about the optimization process. + // + // Description + // Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : + // find the minimum or maximum of f(x) such that + // + // <latex> + // \begin{eqnarray} + // &\mbox{min}_{x} + // & f(x) \\ + // & \text{subject to} & conLB \leq C(x) \leq conUB \\ + // & & lb \leq x \leq ub \\ + // \end{eqnarray} + // </latex> + // + // We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by Ted Ralphs, Menal Guzelsoy and Ashutosh Mahajan. + // + // Examples + // //A basic case : + // // Objective function + // c = [350*5,330*3,310*4,280*6,500,450,400,100] + // // Lower Bound of variable + // lb = repmat(0,1,8); + // // Upper Bound of variables + // ub = [repmat(1,1,4) repmat(%inf,1,4)]; + // // Constraint Matrix + // conMatrix = [5,3,4,6,1,1,1,1; + // 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03; + // 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;] + // // Lower Bound of constrains + // conlb = [ 25; 1.25; 1.25] + // // Upper Bound of constrains + // conub = [ 25; 1.25; 1.25] + // // Row Matrix for telling symphony that the is integer or not + // isInt = [repmat(%t,1,4) repmat(%f,1,4)]; + // xopt = [1 1 0 1 7.25 0 0.25 3.5] + // fopt = [8495] + // // Calling Symphony + // [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1) + // + // Examples + // // An advanced case where we set some options in symphony + // // This problem is taken from + // // P.C.Chu and J.E.Beasley + // // "A genetic algorithm for the multidimensional knapsack problem", + // // Journal of Heuristics, vol. 4, 1998, pp63-86. + // // The problem to be solved is: + // // Max sum{j=1,...,n} p(j)x(j) + // // st sum{j=1,...,n} r(i,j)x(j) <= b(i) i=1,...,m + // // x(j)=0 or 1 + // // The function to be maximize i.e. P(j) + // p = [ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 .. + // 825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 .. + // 877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 .. + // 957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 .. + // 959 668 507 855 986 831 821 825 868 852 832 828 799 686 .. + // 510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 .. + // 1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632] + // //Constraint Matrix + // conMatrix = [ + // //Constraint 1 + // 42 41 523 215 819 551 69 193 582 375 367 478 162 898 .. + // 550 553 298 577 493 183 260 224 852 394 958 282 402 604 .. + // 164 308 218 61 273 772 191 117 276 877 415 873 902 465 .. + // 320 870 244 781 86 622 665 155 680 101 665 227 597 354 .. + // 597 79 162 998 849 136 112 751 735 884 71 449 266 420 .. + // 797 945 746 46 44 545 882 72 383 714 987 183 731 301 .. + // 718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298; + // //Constraint 2 + // 509 883 229 569 706 639 114 727 491 481 681 948 687 941 .. + // 350 253 573 40 124 384 660 951 739 329 146 593 658 816 .. + // 638 717 779 289 430 851 937 289 159 260 930 248 656 833 .. + // 892 60 278 741 297 967 86 249 354 614 836 290 893 857 .. + // 158 869 206 504 799 758 431 580 780 788 583 641 32 653 .. + // 252 709 129 368 440 314 287 854 460 594 512 239 719 751 .. + // 708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850; + // //Constraint 3 + // 806 361 199 781 596 669 957 358 259 888 319 751 275 177 .. + // 883 749 229 265 282 694 819 77 190 551 140 442 867 283 .. + // 137 359 445 58 440 192 485 744 844 969 50 833 57 877 .. + // 482 732 968 113 486 710 439 747 174 260 877 474 841 422 .. + // 280 684 330 910 791 322 404 403 519 148 948 414 894 147 .. + // 73 297 97 651 380 67 582 973 143 732 624 518 847 113 .. + // 382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ; + // //Constraint 4 + // 404 197 817 1000 44 307 39 659 46 334 448 599 931 776 .. + // 263 980 807 378 278 841 700 210 542 636 388 129 203 110 .. + // 817 502 657 804 662 989 585 645 113 436 610 948 919 115 .. + // 967 13 445 449 740 592 327 167 368 335 179 909 825 614 .. + // 987 350 179 415 821 525 774 283 427 275 659 392 73 896 .. + // 68 982 697 421 246 672 649 731 191 514 983 886 95 846 .. + // 689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322; + // //Constrain 5 + // 475 36 287 577 45 700 803 654 196 844 657 387 518 143 .. + // 515 335 942 701 332 803 265 922 908 139 995 845 487 100 .. + // 447 653 649 738 424 475 425 926 795 47 136 801 904 740 .. + // 768 460 76 660 500 915 897 25 716 557 72 696 653 933 .. + // 420 582 810 861 758 647 237 631 271 91 75 756 409 440 .. + // 483 336 765 637 981 980 202 35 594 689 602 76 767 693 .. + // 893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ; + // ]; + // nbCon = size(conMatrix,1) + // nbVar = size(conMatrix,2) + // // Lower Bound of variables + // lb = repmat(0,1,nbVar) + // // Upper Bound of variables + // ub = repmat(1,1,nbVar) + // // Row Matrix for telling symphony that the is integer or not + // isInt = repmat(%t,1,nbVar) + // // Lower Bound of constrains + // conLB=repmat(0,nbCon,1); + // // Upper Bound of constraints + // conUB=[11927 13727 11551 13056 13460 ]'; + // options = ["time_limit" "25"] + // // The expected solution : + // // Output variables + // xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. + // 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 1 0 .. + // 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0] + // // Optimal value + // fopt = [ 24381 ] + // // Calling Symphony + // [x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options) + // + // Authors + // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + +//To check the number of input and output argument + [lhs , rhs] = argn(); + +//To check the number of argument given by user + if ( rhs < 9 | rhs > 11 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set [9 10 11]"), "Symphony", rhs); + error(errmsg) + end + + nbVar = varargin(1); + nbCon = varargin(2); + objCoef = varargin(3); + isInt = varargin(4); + LB = varargin(5); + UB = varargin(6); + conMatrix = varargin(7); + conLB = varargin(8); + conUB = varargin(9); + + if ( rhs<10 ) then + objSense = 1; + else + objSense = varargin(10); + end + + if (rhs<11) then + options = list(); + else + options = varargin(11); + end + + +//Check the size of constraint which should equal to the number of constraints + if ( size(conMatrix,1) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + +//Check the size of Lower Bound which should equal to the number of variables + if ( size(LB,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + +//Check the size of Upper Bound which should equal to the number of variables + if ( size(UB,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + +//Check the size of constraints of Lower Bound which should equal to the number of constraints + if ( size(conLB,1) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Lower Bound of constraints is not equal to the number of constraints"), "Symphony"); + error(errmsg); + end + +//Check the size of constraints of Upper Bound which should equal to the number of constraints + if ( size(conUB,1) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Upper Bound of constraints is not equal to the number of constraints"), "Symphony"); + error(errmsg); + end + + [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options); + +endfunction diff --git a/macros/symphony_call.bin b/macros/symphony_call.bin Binary files differindex b95e887..5008236 100644 --- a/macros/symphony_call.bin +++ b/macros/symphony_call.bin diff --git a/macros/symphony_call.sci b/macros/symphony_call.sci index ea5f34f..c8323fc 100644 --- a/macros/symphony_call.sci +++ b/macros/symphony_call.sci @@ -16,7 +16,7 @@ function [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB, //Setting Options for the Symphpony setOptions(options); - + //Choosing to launch basic or advanced version if(~issparse(conMatrix)) then sym_loadProblemBasic(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix,conLB,conUB); @@ -26,8 +26,8 @@ function [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB, sym_loadProblem(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix_advanced,conLB,conUB); end - op = sym_solve(); + disp(op); xopt = []; fopt = []; diff --git a/macros/symphony_call.sci~ b/macros/symphony_call.sci~ new file mode 100644 index 0000000..057ba63 --- /dev/null +++ b/macros/symphony_call.sci~ @@ -0,0 +1,52 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +function [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options) + + //Opening Symphony environment + sym_open(); + + //Setting Options for the Symphpony +// setOptions(options); + + //Choosing to launch basic or advanced version + if(~issparse(conMatrix)) then + sym_loadProblemBasic(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix,conLB,conUB); + else + // Changing to Constraint Matrix into sparse matrix + conMatrix_advanced=sparse(conMatrix); + sym_loadProblem(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix_advanced,conLB,conUB); + end + + op = sym_solve(); + disp(op); + + xopt = []; + fopt = []; + status = []; + output = []; + + if (~op) then + xopt = sym_getVarSoln(); + // Symphony gives a row matrix converting it to column matrix + xopt = xopt'; + + fopt = sym_getObjVal(); + end + + status = sym_getStatus(); + + output = struct("Iterations" , []); + + output.Iterations = sym_getIterCount(); + + +endfunction diff --git a/macros/symphonymat.bin b/macros/symphonymat.bin Binary files differnew file mode 100644 index 0000000..5089973 --- /dev/null +++ b/macros/symphonymat.bin diff --git a/macros/symphonymat.sci b/macros/symphonymat.sci new file mode 100644 index 0000000..ef70b7c --- /dev/null +++ b/macros/symphonymat.sci @@ -0,0 +1,242 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +function [xopt,fopt,status,iter] = symphonymat (varargin) + // Solves a mixed integer linear programming constrained optimization problem in intlinprog format. + // + // Calling Sequence + // xopt = symphonymat(f,intcon,A,b) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub,options) + // [xopt,fopt,status,output] = symphonymat( ... ) + // + // Parameters + // f : a 1xn matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective + // intcon : Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable + // A : Linear inequality constraint matrix, specified as a matrix of doubles. A represents the linear coefficients in the constraints A*x ≤ b. A has size M-by-N, where M is the number of constraints and N is number of variables + // b : Linear inequality constraint vector, specified as a vector of doubles. b represents the constant vector in the constraints A*x ≤ b. b has length M, where A is M-by-N + // Aeq : Linear equality constraint matrix, specified as a matrix of doubles. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has size Meq-by-N, where Meq is the number of constraints and N is number of variables + // beq : Linear equality constraint vector, specified as a vector of doubles. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N. + // lb : Lower bounds, specified as a vector or array of doubles. lb represents the lower bounds elementwise in lb ≤ x ≤ ub. + // ub : Upper bounds, specified as a vector or array of doubles. ub represents the upper bounds elementwise in lb ≤ x ≤ ub. + // options : a list containing the the parameters to be set. + // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem + // fopt : a 1x1 matrix of doubles, the function value at x + // output : The output data structure contains detailed informations about the optimization process. + // + // Description + // Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : + // find the minimum or maximum of f(x) such that + // + // <latex> + // \begin{eqnarray} + // &\mbox{min}_{x} + // & f(x) \\ + // & \text{subject to} & conLB \leq C(x) \leq conUB \\ + // & & lb \leq x \leq ub \\ + // \end{eqnarray} + // </latex> + // + // We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by Ted Ralphs, Menal Guzelsoy and Ashutosh Mahajan. + // + // Examples + // // Objective function + // c = [350*5,330*3,310*4,280*6,500,450,400,100] + // // Lower Bound of variable + // lb = repmat(0,1,8); + // // Upper Bound of variables + // ub = [repmat(1,1,4) repmat(%inf,1,4)]; + // // Constraint Matrix + // Aeq = [5,3,4,6,1,1,1,1; + // 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03; + // 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;] + // beq = [ 25, 1.25, 1.25] + // intcon = [1 2 3 4]; + // // Calling Symphony + // [x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub) + // + // Examples + // // An advanced case where we set some options in symphony + // // This problem is taken from + // // P.C.Chu and J.E.Beasley + // // "A genetic algorithm for the multidimensional knapsack problem", + // // Journal of Heuristics, vol. 4, 1998, pp63-86. + // // The problem to be solved is: + // // Max sum{j=1,...,n} p(j)x(j) + // // st sum{j=1,...,n} r(i,j)x(j) <= b(i) i=1,...,m + // // x(j)=0 or 1 + // // The function to be maximize i.e. P(j) + // objCoef = -1*[ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 .. + // 825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 .. + // 877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 .. + // 957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 .. + // 959 668 507 855 986 831 821 825 868 852 832 828 799 686 .. + // 510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 .. + // 1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632] + // //Constraint Matrix + // conMatrix = [ //Constraint 1 + // 42 41 523 215 819 551 69 193 582 375 367 478 162 898 .. + // 550 553 298 577 493 183 260 224 852 394 958 282 402 604 .. + // 164 308 218 61 273 772 191 117 276 877 415 873 902 465 .. + // 320 870 244 781 86 622 665 155 680 101 665 227 597 354 .. + // 597 79 162 998 849 136 112 751 735 884 71 449 266 420 .. + // 797 945 746 46 44 545 882 72 383 714 987 183 731 301 .. + // 718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298; + // //Constraint 2 + // 509 883 229 569 706 639 114 727 491 481 681 948 687 941 .. + // 350 253 573 40 124 384 660 951 739 329 146 593 658 816 .. + // 638 717 779 289 430 851 937 289 159 260 930 248 656 833 .. + // 892 60 278 741 297 967 86 249 354 614 836 290 893 857 .. + // 158 869 206 504 799 758 431 580 780 788 583 641 32 653 .. + // 252 709 129 368 440 314 287 854 460 594 512 239 719 751 .. + // 708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850; + // //Constraint 3 + // 806 361 199 781 596 669 957 358 259 888 319 751 275 177 .. + // 883 749 229 265 282 694 819 77 190 551 140 442 867 283 .. + // 137 359 445 58 440 192 485 744 844 969 50 833 57 877 .. + // 482 732 968 113 486 710 439 747 174 260 877 474 841 422 .. + // 280 684 330 910 791 322 404 403 519 148 948 414 894 147 .. + // 73 297 97 651 380 67 582 973 143 732 624 518 847 113 .. + // 382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ; + // //Constraint 4 + // 404 197 817 1000 44 307 39 659 46 334 448 599 931 776 .. + // 263 980 807 378 278 841 700 210 542 636 388 129 203 110 .. + // 817 502 657 804 662 989 585 645 113 436 610 948 919 115 .. + // 967 13 445 449 740 592 327 167 368 335 179 909 825 614 .. + // 987 350 179 415 821 525 774 283 427 275 659 392 73 896 .. + // 68 982 697 421 246 672 649 731 191 514 983 886 95 846 .. + // 689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322; + // //Constrain 5 + // 475 36 287 577 45 700 803 654 196 844 657 387 518 143 .. + // 515 335 942 701 332 803 265 922 908 139 995 845 487 100 .. + // 447 653 649 738 424 475 425 926 795 47 136 801 904 740 .. + // 768 460 76 660 500 915 897 25 716 557 72 696 653 933 .. + // 420 582 810 861 758 647 237 631 271 91 75 756 409 440 .. + // 483 336 765 637 981 980 202 35 594 689 602 76 767 693 .. + // 893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ; + // ]; + // nbVar = size(objCoef,2) + // conUB=[11927 13727 11551 13056 13460 ]; + // // Lower Bound of variables + // lb = repmat(0,1,nbVar) + // // Upper Bound of variables + // ub = repmat(1,1,nbVar) + // // Lower Bound of constrains + // intcon = [] + // for i = 1:nbVar + // intcon = [intcon i]; + // end + // options = list("time_limit", 25); + // // The expected solution : + // // Output variables + // xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. + // 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 .. + // 0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0] + // // Optimal value + // fopt = [ 24381 ] + // // Calling Symphony + // [x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options); + // + // Authors + // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + + +//To check the number of input and output argument + [lhs , rhs] = argn(); + +//To check the number of argument given by user + if ( rhs < 4 | rhs == 5 | rhs == 7 | rhs > 9 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set [4 6 8 9]"), "Symphony", rhs); + error(errmsg) + end + + + objCoef = varargin(1) + intcon = varargin(2) + A = varargin(3) + b = varargin(4) + + nbVar = size(objCoef,2); + nbCon = size(A,1); + + if ( rhs<4 ) then + Aeq = [] + beq = [] + else + Aeq = varargin(5); + beq = varargin(6); + + if (size(Aeq,1)~=0) then + //Check the size of equality constraint which should equal to the number of inequality constraints + if ( size(Aeq,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The size of equality constraint is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + + //Check the size of upper bound of inequality constraint which should equal to the number of constraints + if ( size(beq,2) ~= size(Aeq,1)) then + errmsg = msprintf(gettext("%s: The equality constraint upper bound is not equal to the number of equality constraint"), "Symphony"); + error(errmsg); + end + end + + end + + if ( rhs<6 ) then + lb = repmat(-%inf,1,nbVar); + ub = repmat(%inf,1,nbVar); + else + lb = varargin(7); + ub = varargin(8); + end + + if (rhs<9) then + options = list(); + else + options = varargin(9); + end + + +//Check the size of lower bound of inequality constraint which should equal to the number of constraints + if ( size(b,2) ~= size(A,1)) then + errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraint is not equal to the number of constraint"), "Symphony"); + error(errmsg); + end + +//Check the size of Lower Bound which should equal to the number of variables + if ( size(lb,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + +//Check the size of Upper Bound which should equal to the number of variables + if ( size(ub,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + + //Changing the inputs in symphony's format + conMatrix = [A;Aeq] + nbCon = size(conMatrix,1); + conLB = [repmat(-%inf,1,size(A,1)), beq]'; + conUB = [b,beq]' ; + + isInt = repmat(%f,1,nbVar); + for i=1:size(intcon,2) + isInt(intcon(i)) = %t + end + + objSense = 1; + + [xopt,fopt,status,iter] = symphony_call(nbVar,nbCon,objCoef,isInt,lb,ub,conMatrix,conLB,conUB,objSense,options); + +endfunction diff --git a/macros/symphonymat.sci~ b/macros/symphonymat.sci~ new file mode 100644 index 0000000..455dd67 --- /dev/null +++ b/macros/symphonymat.sci~ @@ -0,0 +1,242 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +function [xopt,fopt,status,iter] = symphonymat (varargin) + // Solves a mixed integer linear programming constrained optimization problem in intlinprog format. + // + // Calling Sequence + // xopt = symphonymat(f,intcon,A,b) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub,options) + // [xopt,fopt,status,output] = symphonymat( ... ) + // + // Parameters + // f : a 1xn matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective + // intcon : Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable + // A : Linear inequality constraint matrix, specified as a matrix of doubles. A represents the linear coefficients in the constraints A*x ≤ b. A has size M-by-N, where M is the number of constraints and N is number of variables + // b : Linear inequality constraint vector, specified as a vector of doubles. b represents the constant vector in the constraints A*x ≤ b. b has length M, where A is M-by-N + // Aeq : Linear equality constraint matrix, specified as a matrix of doubles. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has size Meq-by-N, where Meq is the number of constraints and N is number of variables + // beq : Linear equality constraint vector, specified as a vector of doubles. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N. + // lb : Lower bounds, specified as a vector or array of doubles. lb represents the lower bounds elementwise in lb ≤ x ≤ ub. + // ub : Upper bounds, specified as a vector or array of doubles. ub represents the upper bounds elementwise in lb ≤ x ≤ ub. + // options : a list containing the the parameters to be set. + // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem + // fopt : a 1x1 matrix of doubles, the function value at x + // output : The output data structure contains detailed informations about the optimization process. + // + // Description + // Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : + // find the minimum or maximum of f(x) such that + // + // <latex> + // \begin{eqnarray} + // &\mbox{min}_{x} + // & f(x) \\ + // & \text{subject to} & conLB \leq C(x) \leq conUB \\ + // & & lb \leq x \leq ub \\ + // \end{eqnarray} + // </latex> + // + // We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by Ted Ralphs, Menal Guzelsoy and Ashutosh Mahajan. + // + // Examples + // // Objective function + // c = [350*5,330*3,310*4,280*6,500,450,400,100] + // // Lower Bound of variable + // lb = repmat(0,1,8); + // // Upper Bound of variables + // ub = [repmat(1,1,4) repmat(%inf,1,4)]; + // // Constraint Matrix + // Aeq = [5,3,4,6,1,1,1,1; + // 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03; + // 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;] + // beq = [ 25, 1.25, 1.25] + // intcon = [1 2 3 4]; + // // Calling Symphony + // [x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub) + // + // Examples + // // An advanced case where we set some options in symphony + // // This problem is taken from + // // P.C.Chu and J.E.Beasley + // // "A genetic algorithm for the multidimensional knapsack problem", + // // Journal of Heuristics, vol. 4, 1998, pp63-86. + // // The problem to be solved is: + // // Max sum{j=1,...,n} p(j)x(j) + // // st sum{j=1,...,n} r(i,j)x(j) <= b(i) i=1,...,m + // // x(j)=0 or 1 + // // The function to be maximize i.e. P(j) + // objCoef = -1*[ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 .. + // 825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 .. + // 877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 .. + // 957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 .. + // 959 668 507 855 986 831 821 825 868 852 832 828 799 686 .. + // 510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 .. + // 1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632] + // //Constraint Matrix + // conMatrix = [ //Constraint 1 + // 42 41 523 215 819 551 69 193 582 375 367 478 162 898 .. + // 550 553 298 577 493 183 260 224 852 394 958 282 402 604 .. + // 164 308 218 61 273 772 191 117 276 877 415 873 902 465 .. + // 320 870 244 781 86 622 665 155 680 101 665 227 597 354 .. + // 597 79 162 998 849 136 112 751 735 884 71 449 266 420 .. + // 797 945 746 46 44 545 882 72 383 714 987 183 731 301 .. + // 718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298; + // //Constraint 2 + // 509 883 229 569 706 639 114 727 491 481 681 948 687 941 .. + // 350 253 573 40 124 384 660 951 739 329 146 593 658 816 .. + // 638 717 779 289 430 851 937 289 159 260 930 248 656 833 .. + // 892 60 278 741 297 967 86 249 354 614 836 290 893 857 .. + // 158 869 206 504 799 758 431 580 780 788 583 641 32 653 .. + // 252 709 129 368 440 314 287 854 460 594 512 239 719 751 .. + // 708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850; + // //Constraint 3 + // 806 361 199 781 596 669 957 358 259 888 319 751 275 177 .. + // 883 749 229 265 282 694 819 77 190 551 140 442 867 283 .. + // 137 359 445 58 440 192 485 744 844 969 50 833 57 877 .. + // 482 732 968 113 486 710 439 747 174 260 877 474 841 422 .. + // 280 684 330 910 791 322 404 403 519 148 948 414 894 147 .. + // 73 297 97 651 380 67 582 973 143 732 624 518 847 113 .. + // 382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ; + // //Constraint 4 + // 404 197 817 1000 44 307 39 659 46 334 448 599 931 776 .. + // 263 980 807 378 278 841 700 210 542 636 388 129 203 110 .. + // 817 502 657 804 662 989 585 645 113 436 610 948 919 115 .. + // 967 13 445 449 740 592 327 167 368 335 179 909 825 614 .. + // 987 350 179 415 821 525 774 283 427 275 659 392 73 896 .. + // 68 982 697 421 246 672 649 731 191 514 983 886 95 846 .. + // 689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322; + // //Constrain 5 + // 475 36 287 577 45 700 803 654 196 844 657 387 518 143 .. + // 515 335 942 701 332 803 265 922 908 139 995 845 487 100 .. + // 447 653 649 738 424 475 425 926 795 47 136 801 904 740 .. + // 768 460 76 660 500 915 897 25 716 557 72 696 653 933 .. + // 420 582 810 861 758 647 237 631 271 91 75 756 409 440 .. + // 483 336 765 637 981 980 202 35 594 689 602 76 767 693 .. + // 893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ; + // ]; + // nbVar = size(objCoef,2) + // conUB=[11927 13727 11551 13056 13460 ]; + // // Lower Bound of variables + // lb = repmat(0,1,nbVar) + // // Upper Bound of variables + // ub = repmat(1,1,nbVar) + // // Lower Bound of constrains + // intcon = [] + // for i = 1:nbVar + // intcon = [intcon i]; + // end + // options = list("time_limit", 25); + // // The expected solution : + // // Output variables + // xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. + // 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 .. + // 0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0] + // // Optimal value + // fopt = [ 24381 ] + // // Calling Symphony + // [x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options); + // + // Authors + // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + + +//To check the number of input and output argument + [lhs , rhs] = argn(); + +//To check the number of argument given by user + if ( rhs < 4 | rhs == 5 | rhs == 7 | rhs > 9 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set [4 6 8 9]"), "Symphony", rhs); + error(errmsg) + end + + + objCoef = varargin(1) + intcon = varargin(2) + A = varargin(3) + b = varargin(4) + + nbVar = size(objCoef,2); + nbCon = size(A,1); + + if ( rhs<4 ) then + Aeq = [] + beq = [] + else + Aeq = varargin(5); + beq = varargin(6); + + if (size(Aeq,1)~=0) then + //Check the size of equality constraint which should equal to the number of inequality constraints + if ( size(Aeq,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The size of equality constraint is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + + //Check the size of upper bound of inequality constraint which should equal to the number of constraints + if ( size(beq,2) ~= size(Aeq,1)) then + errmsg = msprintf(gettext("%s: The equality constraint upper bound is not equal to the number of equality constraint"), "Symphony"); + error(errmsg); + end + end + + end + + if ( rhs<6 ) then + lb = repmat(-%inf,1,nbVar); + ub = repmat(%inf,1,nbVar); + else + lb = varargin(7); + ub = varargin(8); + end + + if (rhs<8) then + options = list(); + else + options = varargin(9); + end + + +//Check the size of lower bound of inequality constraint which should equal to the number of constraints + if ( size(b,2) ~= size(A,1)) then + errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraint is not equal to the number of constraint"), "Symphony"); + error(errmsg); + end + +//Check the size of Lower Bound which should equal to the number of variables + if ( size(lb,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + +//Check the size of Upper Bound which should equal to the number of variables + if ( size(ub,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + + //Changing the inputs in symphony's format + conMatrix = [A;Aeq] + nbCon = size(conMatrix,1); + conLB = [repmat(-%inf,1,size(A,1)), beq]'; + conUB = [b,beq]' ; + + isInt = repmat(%f,1,nbVar); + for i=1:size(intcon,2) + isInt(intcon(i)) = %t + end + + objSense = 1; + + [xopt,fopt,status,iter] = symphony_call(nbVar,nbCon,objCoef,isInt,lb,ub,conMatrix,conLB,conUB,objSense,options); + +endfunction |