ex_doc_sparseformat.m

来自「HERE IS A GOOD PSO TOOL BOX」· M 代码 · 共 71 行

%----------------------------------------------------------------------
%
%       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 (SPARSE FORMAT)
%----------------------------------------------------------------------

A0 = sparse(3,3);
A1 = sparse(2,3);
A2 = sparse(3,3);

  A0(1,1) = -1;
  A0(1,2) = -0.5;
  A0(1,3) = -1;
  A0(2,1) =  1;
  A0(2,3) =  1;
  A0(3,1) =  1;
  A0(3,2) =  1;
  A0(3,3) =  1;

  A1(1,1) = -2;
  A1(1,2) = -2;
  A1(2,2) =  0.5;
  A1(2,3) = -1;

  A2(1,1) =  1;
  A2(2,2) =  1;
  A2(3,3) =  1;

A   = [  A0;  A1;  A2 ];

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

G  = sparse(1,3);

  G(1,1)  = 1;
  G(1,2)  = 1;

b   = [  b0;  b1;  b2 ];
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)