Builds and solves a simple inequality-constrained linear program

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

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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.
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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 :            8.65E+00 0.000
  1 :   2.40E+00 2.79E+00 0.000 0.3230 0.9000 0.9000   0.77  1  1  9.1E+00
  2 :   1.34E+00 8.68E-01 0.000 0.3110 0.9000 0.9000   0.35  1  1  4.6E+00
  3 :   3.31E-01 4.19E-02 0.000 0.0482 0.9900 0.9900  -0.60  1  1  3.9E+00
  4 :   2.03E-01 8.51E-06 0.000 0.0002 0.9999 0.9999  -0.98  1  1  
Dual infeasible, primal improving direction found.
iter seconds  |Ax|    [Ay]_+     |x|       |y|
  4      0.0   3.9e-15   1.8e-20   8.9e+00   1.2e-20

Detailed timing (sec)
   Pre          IPM          Post
1.000E-02    1.000E-02    0.000E+00    
Max-norms: ||b||=2.818197e+00, ||c|| = 2.154474e+00,
Cholesky |add|=0, |skip| = 0, ||L.L|| = 1.
------------------------------------------------------------
Status: Infeasible
Optimal value (cvx_optval): +Inf

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