% Boyd & Vandenberghe "Convex Optimization"
% Joëlle Skaf - 04/29/08
%
% The analytic center of a set of linear inequalities and equalities:
%           a_i^Tx <= b_i   i=1,...,m,
%           Fx = g,
% is the solution of the unconstrained minimization problem
%           minimize    -sum_{i=1}^m log(b_i-a_i^Tx).

% Input data
randn('state', 0);
rand('state', 0);
n = 10;
m = 50;
p = 5;
tmp = randn(n,1);
A = randn(m,n);
b = A*tmp + 10*rand(m,1);
F = randn(p,n);
g = F*tmp;

% Analytic center
cvx_begin
    variable x(n)
    minimize -sum(log(b-A*x))
    F*x == g
cvx_end

disp(['The analytic center of the set of linear inequalities and ' ...
      'equalities is: ']);
disp(x);

 
Successive approximation method to be employed.
   SDPT3 will be called several times to refine the solution.
   Original size: 160 variables, 105 equality constraints
   50 exponentials add 400 variables, 250 equality constraints
-----------------------------------------------------------------
 Cones  |             Errors              |
Mov/Act | Centering  Exp cone   Poly cone | Status
--------+---------------------------------+---------
 50/ 50 | 2.435e+00  3.573e-01  0.000e+00 | Solved
 50/ 50 | 1.982e-01  3.069e-03  0.000e+00 | Solved
 49/ 49 | 2.535e-02  4.842e-05  0.000e+00 | Solved
 11/ 46 | 1.342e-03  1.284e-07  0.000e+00 | Solved
  0/  6 | 1.582e-04  1.762e-09  0.000e+00 | Solved
-----------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): -64.8504
 
The analytic center of the set of linear inequalities and equalities is: 
   -0.3618
   -1.5333
    0.1387
    0.2491
   -1.1163
    1.3142
    1.2303
   -0.0511
    0.4031
    0.1248