echo on n = 10; A = randn(2*n,n); b = randn(2*n,1); c = randn(n,1); d = randn; cvx_begin variable x(n) dual variables y z minimize( c' * x + d ) subject to y : A * x <= b; cvx_end echo off
n = 10; A = randn(2*n,n); b = randn(2*n,1); c = randn(n,1); d = randn; cvx_begin variable x(n) dual variables y z minimize( c' * x + d ) subject to y : A * x <= b; cvx_end Calling sedumi: 20 variables, 10 equality constraints For improved efficiency, sedumi is solving the dual problem. ------------------------------------------------------------ SeDuMi 1.21 by AdvOL, 2005-2008 and Jos F. Sturm, 1998-2003. Alg = 2: xz-corrector, Adaptive Step-Differentiation, theta = 0.250, beta = 0.500 eqs m = 10, order n = 21, dim = 21, blocks = 1 nnz(A) = 200 + 0, nnz(ADA) = 100, nnz(L) = 55 it : b*y gap delta rate t/tP* t/tD* feas cg cg prec 0 : 4.71E+00 0.000 1 : 1.34E+01 1.22E+00 0.000 0.2587 0.9000 0.9000 -1.79 1 1 3.1E+01 2 : 6.72E+01 3.27E-01 0.000 0.2688 0.9000 0.9000 -0.78 1 1 2.0E+01 3 : 1.36E+03 1.14E-02 0.000 0.0347 0.9900 0.9900 -0.79 1 1 1.2E+01 4 : 2.96E+07 5.42E-07 0.077 0.0000 1.0000 1.0000 -1.00 1 1 Primal infeasible, dual improving direction found. iter seconds |Ax| [Ay]_+ |x| |y| 4 0.0 0.0e+00 0.0e+00 0.0e+00 7.0e-01 Detailed timing (sec) Pre IPM Post 1.000E-02 1.000E-02 0.000E+00 Max-norms: ||b||=1.576658e+00, ||c|| = 2.453744e+00, Cholesky |add|=0, |skip| = 0, ||L.L|| = 1. ------------------------------------------------------------ Status: Unbounded Optimal value (cvx_optval): -Inf echo off