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diff --git a/macros/qpipopt.sci b/macros/qpipopt.sci index ed531e1..e8c945a 100644 --- a/macros/qpipopt.sci +++ b/macros/qpipopt.sci @@ -1,108 +1,109 @@ // 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 +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) - // Solves a linear quadratic problem. - // - // Calling Sequence - // xopt = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB) - // xopt = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0) - // xopt = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0,param) - // [xopt,fopt,exitflag,output,lamda] = qpipopt( ... ) - // - // Parameters - // nbVar : a double, number of variables - // nbCon : a double, number of constraints - // H : a symmetric matrix of double, represents coefficients of quadratic in the quadratic problem. - // f : a vector of double, represents coefficients of linear in the quadratic problem - // lb : a vector of double, contains lower bounds of the variables. - // ub : a vector of double, contains upper bounds of the variables. - // A : a matrix of double, contains matrix representing the constraint matrix - // conLB : a vector of double, contains lower bounds of the constraints. - // conUB : a vector of double, contains upper bounds of the constraints. - // x0 : a vector of double, contains initial guess of variables. - // param : a list containing the the parameters to be set. - // xopt : a vector of double, the computed solution of the optimization problem. - // fopt : a double, the function value at x. - // exitflag : Integer identifying the reason the algorithm terminated. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the qpipopt macro. - // output : Structure containing information about the optimization. This version only contains number of iterations - // lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints. - // - // Description - // 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^T⋅H⋅x + f^T⋅x \\ - // & \text{subject to} & conLB \leq A⋅x \leq conUB \\ - // & & lb \leq x \leq ub \\ - // \end{eqnarray} - // </latex> - // - // The routine calls Ipopt for solving the quadratic problem, Ipopt is a library written in C++. - // - // Examples - // //Find x in R^6 such that: - // A= [1,-1,1,0,3,1; - // -1,0,-3,-4,5,6; - // 2,5,3,0,1,0 - // 0,1,0,1,2,-1; - // -1,0,2,1,1,0]; - // conLB=[1;2;3;-%inf;-%inf]; - // conUB = [1;2;3;-1;2.5]; - // lb=[-1000;-10000; 0; -1000; -1000; -1000]; - // ub=[10000; 100; 1.5; 100; 100; 1000]; - // //and minimize 0.5*x'⋅H⋅x + f'⋅x with - // f=[1; 2; 3; 4; 5; 6]; H=eye(6,6); - // nbVar = 6; - // nbCon = 5; - // x0 = repmat(0,nbVar,1); - // param = list("MaxIter", 300, "CpuTime", 100); - // [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0,param) - // // Press ENTER to continue - // - // 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]; - // 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,H,f,lb,ub,A,conLB,conUB) - // Authors - // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + // Solves a linear quadratic problem. + // + // Calling Sequence + // xopt = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB) + // xopt = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0) + // xopt = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0,param) + // [xopt,fopt,exitflag,output,lamda] = qpipopt( ... ) + // + // Parameters + // nbVar : a double, number of variables + // nbCon : a double, number of constraints + // H : a symmetric matrix of double, represents coefficients of quadratic in the quadratic problem. + // f : a vector of double, represents coefficients of linear in the quadratic problem + // lb : a vector of double, contains lower bounds of the variables. + // ub : a vector of double, contains upper bounds of the variables. + // A : a matrix of double, contains matrix representing the constraint matrix + // conLB : a vector of double, contains lower bounds of the constraints. + // conUB : a vector of double, contains upper bounds of the constraints. + // x0 : a vector of double, contains initial guess of variables. + // param : a list containing the the parameters to be set. + // xopt : a vector of double, the computed solution of the optimization problem. + // fopt : a double, the function value at x. + // exitflag : A flag showing returned exit flag from Ipopt. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the lsqlin macro. + // output : Structure containing information about the optimization. This version only contains number of iterations + // lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper bound multiplier and linear equality, inequality constraint multiplier. + // + // Description + // Search the minimum of a constrained linear quadratic optimization problem specified by : + // + // <latex> + // \begin{eqnarray} + // &\mbox{min}_{x} + // & 1/2⋅x^T⋅H⋅x + f^T⋅x \\ + // & \text{subject to} & conLB \leq A⋅x \leq conUB \\ + // & & lb \leq x \leq ub \\ + // \end{eqnarray} + // </latex> + // + // The routine calls Ipopt for solving the quadratic problem, Ipopt is a library written in C++. + // + // Examples + // //Ref : example 14 : + // //https://www.me.utexas.edu/~jensen/ORMM/supplements/methods/nlpmethod/S2_quadratic.pdf + // // min. -8*x1*x1 -16*x2*x2 + x1 + 4*x2 + // // such that + // // x1 + x2 <= 5, + // // x1 <= 3, + // // x1 >= 0, + // // x2 >= 0 + // H = [2 0 + // 0 8]; + // f = [-8; -16]; + // A = [1 1;1 0]; + // conUB = [5;3]; + // conLB = [-%inf; -%inf]; + // lb = [0; 0]; + // ub = [%inf; %inf]; + // nbVar = 2; + // nbCon = 2; + // [xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB) + // //Press ENTER to continue + // + // Examples + // //Find x in R^6 such that: + // A= [1,-1,1,0,3,1; + // -1,0,-3,-4,5,6; + // 2,5,3,0,1,0 + // 0,1,0,1,2,-1; + // -1,0,2,1,1,0]; + // conLB=[1;2;3;-%inf;-%inf]; + // conUB = [1;2;3;-1;2.5]; + // lb=[-1000;-10000; 0; -1000; -1000; -1000]; + // ub=[10000; 100; 1.5; 100; 100; 1000]; + // //and minimize 0.5*x'⋅H⋅x + f'⋅x with + // f=[1; 2; 3; 4; 5; 6]; H=eye(6,6); + // nbVar = 6; + // nbCon = 5; + // x0 = repmat(0,nbVar,1); + // param = list("MaxIter", 300, "CpuTime", 100); + // [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0,param) + // Authors + // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh -//To check the number of input and output argument - [lhs , rhs] = argn(); + //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 - + //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 = []; nbCon = []; H = []; |