# on convergence in optimization [closed]

I am trying to solve a nonlinear programming problem using FindMinimum solver on Mathematica. When I execute, it is printing

FindMinimum::eit: "The algorithm does not converge to the tolerance of 4.806217383937354*^-6 in 500 iterations. The best estimated solution, with feasibility residual, KKT residual, or complementary residual of {0.00499384,0.00461499,2.68875*10^-6}, is returned"

Can we still use this solution for when I calculate one of the constraints using printed data, it is outside the defined range?

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## closed as off-topic by Yves Klett, Michael E2, bobthechemist, belisarius, ÖskåJul 21 '14 at 17:58

This question appears to be off-topic. The users who voted to close gave this specific reason:

• "This question cannot be answered without additional information. Questions on problems in code must describe the specific problem and include valid code to reproduce it. Any data used for programming examples should be embedded in the question or code to generate the (fake) data must be included." – Michael E2, bobthechemist, belisarius, Öskå
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"Can we still use this solution for when I calculate one of the constraints using printed data, it is outside the defined range?" does not really make sense to me. Could you clarify? Also, why have you used the linearprogramming tag for a nonlinear optimization problem? –  Oleksandr R. Jul 21 '14 at 10:17
Thank you for the response. Even though the algorithm isn't convergent it is returning desired solution to the parameters. My question is is the solution reliable considering 500 iterations? –  user31694 Jul 21 '14 at 12:35
Your judgment is required to say whether it is reliable or not. FindMinimum` provides you with three different measures of the degree of convergence. From what you know about the problem, and the use to which you intend to put the result, is it good enough, or not? Nobody else can tell you this. If you want more concrete advice from others, I'm afraid you'll have to ask a more concrete question. –  Oleksandr R. Jul 21 '14 at 12:53
Are you looking for a local minimum? If not, you should use Minimize or NMinimize. –  Karsten 7. Jul 21 '14 at 12:56
@Karsten7. No, I am looking for global minimum. But Minimize and NMinimize are giving errors. FindMinimum gave descent results. One question, can we give our own range for objective fn. for example 0<x+y<1 as a constraint? –  user31694 Jul 21 '14 at 17:41