rand('state',1)
L = 20;
n = 10;
k = 7;
A = double(rand(L,n) <= k/L);
c = 0.9*rand(L,1)+0.1;
cvx_begin
variable x(n);
maximize(sum(log(x)))
subject to
A*x <= c
cvx_end
primal_obj = cvx_optval;
cvx_begin
variable lambda(L);
minimize(c'*lambda-sum(log(A'*lambda))-n)
subject to
lambda >= 0
cvx_end
dual_obj = cvx_optval;
Successive approximation method to be employed.
SDPT3 will be called several times to refine the solution.
Original size: 50 variables, 30 equality constraints
10 exponentials add 80 variables, 50 equality constraints
-----------------------------------------------------------------
Cones | Errors |
Mov/Act | Centering Exp cone Poly cone | Status
--------+---------------------------------+---------
10/ 10 | 2.835e+00 8.576e-01 0.000e+00 | Solved
10/ 10 | 9.542e-01 7.939e-02 0.000e+00 | Solved
10/ 10 | 1.666e-01 2.253e-03 0.000e+00 | Solved
10/ 10 | 2.204e-02 3.875e-05 0.000e+00 | Solved
9/ 10 | 2.601e-03 5.374e-07 0.000e+00 | Solved
0/ 7 | 3.015e-04 6.607e-09 0.000e+00 | Solved
-----------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): -31.5685
Successive approximation method to be employed.
SDPT3 will be called several times to refine the solution.
Original size: 50 variables, 20 equality constraints
10 exponentials add 80 variables, 50 equality constraints
-----------------------------------------------------------------
Cones | Errors |
Mov/Act | Centering Exp cone Poly cone | Status
--------+---------------------------------+---------
10/ 10 | 5.283e+00 1.547e+00 1.450e-09 | Solved
10/ 10 | 1.412e+00 1.312e-01 2.806e-09 | Solved
10/ 10 | 1.306e-01 1.080e-03 2.898e-09 | Solved
10/ 10 | 1.689e-02 1.815e-05 2.609e-09 | Solved
10/ 10 | 2.271e-03 3.237e-07 2.635e-09 | Solved
0/ 7 | 3.067e-04 4.624e-09 2.633e-09 | Solved
-----------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): -31.5685