diff options
Diffstat (limited to 'macros')
| -rw-r--r-- | macros/lib | bin | 432 -> 456 bytes | |||
| -rw-r--r-- | macros/names | 1 | ||||
| -rw-r--r-- | macros/qpipopt.bin | bin | 0 -> 26088 bytes | |||
| -rw-r--r-- | macros/qpipopt.sci | 174 | ||||
| -rw-r--r-- | macros/symphony.bin | bin | 42972 -> 43716 bytes | |||
| -rw-r--r-- | macros/symphony.sci | 8 | ||||
| -rw-r--r-- | macros/symphony_mat.bin | bin | 45392 -> 45744 bytes | |||
| -rw-r--r-- | macros/symphony_mat.sci | 20 |
8 files changed, 189 insertions, 14 deletions
| Binary files differ diff --git a/macros/names b/macros/names index ad89db2..da92859 100644 --- a/macros/names +++ b/macros/names @@ -1,3 +1,4 @@ +qpipopt setOptions symphony symphony_call diff --git a/macros/qpipopt.bin b/macros/qpipopt.bin Binary files differnew file mode 100644 index 0000000..594d645 --- /dev/null +++ b/macros/qpipopt.bin diff --git a/macros/qpipopt.sci b/macros/qpipopt.sci new file mode 100644 index 0000000..0d1b6b6 --- /dev/null +++ b/macros/qpipopt.sci @@ -0,0 +1,174 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + + +function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) + // Solves a linear quadratic problem. + // + // Calling Sequence + // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) + // [xopt,fopt,exitflag,output,lamda] = qpipopt( ... ) + // + // Parameters + // nbVar : a 1 x 1 matrix of doubles, number of variables + // nbCon : a 1 x 1 matrix of doubles, number of constraints + // Q : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. + // p : a 1 x n matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem + // LB : a 1 x n matrix of doubles, where n is number of variables, contains lower bounds of the variables. + // UB : a 1 x n matrix of doubles, where n is number of variables, contains upper bounds of the variables. + // conMatrix : a m x n matrix of doubles, where n is number of variables and m is number of constraints, contains matrix representing the constraint matrix + // conLB : a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints. + // conUB : a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints. + // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem. + // fopt : a 1x1 matrix of doubles, the function value at x. + // exitflag : Integer identifying the reason the algorithm terminated. + // output : Structure containing information about the optimization. + // lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type). + // + // Description + // Search the minimum of a constrained linear quadratic optimization problem specified by : + // find the minimum of f(x) such that + // + // <latex> + // \begin{eqnarray} + // &\mbox{min}_{x} + // & 1/2*x'*Q*x + p'*x \\ + // & \text{subject to} & conLB \leq C(x) \leq conUB \\ + // & & lb \leq x \leq ub \\ + // \end{eqnarray} + // </latex> + // + // We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by Andreas Wächter and Carl Laird. + // + // Examples + // //Find x in R^6 such that: + // + // conMatrix= [1,-1,1,0,3,1; + // -1,0,-3,-4,5,6; + // 2,5,3,0,1,0 + // 0,1,0,1,2,-1; + // -1,0,2,1,1,0]; + // conLB=[1 2 3 -%inf -%inf]'; + // conUB = [1 2 3 -1 2.5]'; + // //with x between ci and cs: + // lb=[-1000 -10000 0 -1000 -1000 -1000]; + // ub=[10000 100 1.5 100 100 1000]; + // //and minimize 0.5*x'*Q*x + p'*x with + // p=[1 2 3 4 5 6]; Q=eye(6,6); + // nbVar = 6; + // nbCon = 5; + // [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) + // + // Examples + // //min. -8*x1 -16*x2 + x1^2 + 4* x2^2 + // // such that + // // x1 + x2 <= 5, + // // x1 <= 3, + // // x1 >= 0, + // // x2 >= 0 + // conMatrix= [1 1]; + // conLB=[-%inf]; + // conUB = [5]; + // //with x between ci and cs: + // lb=[0,0]; + // ub=[3,%inf]; + // //and minimize 0.5*x'*Q*x + p'*x with + // p=[-8,-16]; + // Q=[1,0;0,4]; + // nbVar = 2; + // nbCon = 1; + // [xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) + // + // Authors + // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + + +//To check the number of input and output argument + [lhs , rhs] = argn(); + +//To check the number of argument given by user + if ( rhs ~= 9 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9"), "qpipopt", rhs); + error(errmsg) + end + + + nbVar = varargin(1); + nbCon = varargin(2); + Q = varargin(3); + p = varargin(4); + LB = varargin(5); + UB = varargin(6); + conMatrix = varargin(7); + conLB = varargin(8); + conLB = conLB'; //IPOpt wants it in row matrix form + conUB = varargin(9); + conUB = conUB'; //IPOpt wants it in row matrix form + + //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 constraints + if ( size(conMatrix,1) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + +//Check the size of Lower Bound which should equal to the number of variables + if ( size(LB,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + +//Check the size of Upper Bound which should equal to the number of variables + if ( size(UB,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + +//Check the size of constraints of Lower Bound which should equal to the number of constraints + if ( size(conLB,2) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Lower Bound of constraints is not equal to the number of constraints"), "qpipopt"); + error(errmsg); + end + +//Check the size of constraints of Upper Bound which should equal to the number of constraints + if ( size(conUB,2) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Upper Bound of constraints is not equal to the number of constraints"), "qp_ipopt"); + error(errmsg); + end + + [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB); + + xopt = xopt'; + exitflag = status; + output = struct("Iterations" , []); + output.Iterations = iter; + lambda = struct("lower" , [], .. + "upper" , [], .. + "constraint" , []); + + lambda.lower = Zl; + lambda.upper = Zu; + lambda.constraint = lmbda; + + +endfunction diff --git a/macros/symphony.bin b/macros/symphony.bin Binary files differindex e82e907..ae6c958 100644 --- a/macros/symphony.bin +++ b/macros/symphony.bin diff --git a/macros/symphony.sci b/macros/symphony.sci index 18ab5e1..f221160 100644 --- a/macros/symphony.sci +++ b/macros/symphony.sci @@ -16,7 +16,7 @@ function [xopt,fopt,status,output] = symphony (varargin) // 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,iter] = symphony( ... ) + // [xopt,fopt,status,output] = symphony( ... ) // // Parameters // nbVar : a 1 x 1 matrix of doubles, number of variables @@ -43,12 +43,12 @@ function [xopt,fopt,status,output] = symphony (varargin) // \begin{eqnarray} // &\mbox{min}_{x} // & f(x) \\ - // & \text{subject to} & conLB \geq C(x) \leq conUB \\ - // & & lb \geq x \leq ub \\ + // & \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 : diff --git a/macros/symphony_mat.bin b/macros/symphony_mat.bin Binary files differindex bcc2d01..3b72644 100644 --- a/macros/symphony_mat.bin +++ b/macros/symphony_mat.bin diff --git a/macros/symphony_mat.sci b/macros/symphony_mat.sci index dc11101..068e9cf 100644 --- a/macros/symphony_mat.sci +++ b/macros/symphony_mat.sci @@ -17,7 +17,7 @@ function [xopt,fopt,status,iter] = symphony_mat (varargin) // xopt = symphony_mat(f,intcon,A,b,Aeq,beq) // xopt = symphony_mat(f,intcon,A,b,Aeq,beq,lb,ub) // xopt = symphony_mat(f,intcon,A,b,Aeq,beq,lb,ub,options) - // [xopt,fopt,iter] = symphony_mat( ... ) + // [xopt,fopt,status,output] = symphony_mat( ... ) // // Parameters // f : a 1xn matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective @@ -31,22 +31,22 @@ function [xopt,fopt,status,iter] = symphony_mat (varargin) // 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 - // iter : a 1x1 matrix of doubles, contains the number od iterations done by 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) \\ - // \mbox{subject to} & c(x) \leq 0 \\ - // & c_{eq}(x) = 0 \\ - // & Ax \leq b \\ - // & A_{eq} x = b_{eq} \\ - // & lb \leq x \leq ub + // \begin{eqnarray} + // &\mbox{min}_{x} + // & f(x) \\ + // & \text{subject to} & conLB \leq C(x) \leq conUB \\ + // & & lb \leq x \leq ub \\ // \end{eqnarray} - // </latex> + // </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 |