ex_doc_denseformat.m

HERE IS A GOOD PSO TOOL BOX

%----------------------------------------------------------------------
%
%       GP EXAMPLE IN THE DOCUMENT
%
%----------------------------------------------------------------------
%
%   minimize:   x^-1*y^-0.5*z^-1 + 2.3*x*z + 4*x*y*z
%   subject to: (1/3)*x^-2*y^-2 + (4/3)*y^0.5*z^-1 <= 1
%               0.1*x + 0.2*y + 0.3*z <= 1
%               (1/2)*x*y = 1; 
%
%   This is an example shown in the documentation of gpcvx and gpposy
%   (see gpposy.ps and gpcvx.ps in doc directory).
%

clear all; close all;

%----------------------------------------------------------------------
%      PROBLEM DATA IN POSYNOMIAL FORM (DENSE FORMAT)
%----------------------------------------------------------------------

A0  = [  -1 -0.5   -1 ;...
          1    0    1 ;...
          1    1    1 ];
A1  = [  -2   -2    0 ;...
          0  0.5   -1 ];
A2  = [   1    0    0 ;...
          0    1    0 ;...
          0    0    1 ];
A   = [  A0;  A1;  A2 ];

b0  = [   1; 2.3;   4 ];
b1  = [ 1/3; 4/3 ];
b2  = [ 0.1; 0.2; 0.3 ];

b   = [  b0;  b1;  b2 ];

G   = [   1    1    0 ];

h   = 0.5;

szs = [ size(A0,1); size(A1,1); size(A2,1) ];

%----------------------------------------------------------------------
%      SOLVE THE PROBLEM IN POSYNOMIAL FORM
%----------------------------------------------------------------------
[x1,status1,lambda1,nu1] = gpposy(A,b,szs,G,h);
sol_posy = x1

%----------------------------------------------------------------------
%      SOLVE THE PROBLEM IN CONVEX FORM
%----------------------------------------------------------------------
[x2,status2,lambda2,nu2,mu2] = gpcvx(A,log(b),szs,G,log(h));
sol_cvx = exp(x2)