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Hi
This is my problem.
'Presolve eliminates 344 constraints and 438 variables.
Substitution eliminates 978 variables.
Adjusted problem:
134 variables:
126 nonlinear variables
8 linear variables
52 constraints; 838 nonzeros
38 nonlinear constraints
14 linear constraints
20 equality constraints
32 inequality constraints
1 nonlinear objective; 134 nonzeros.'
The problem also has ceiling function with variable inside it and different places.
Thanks
Harprinder
On Tue, Jul 2, 2019 at 1:38 PM UTC, AMPL Modeling Language <am...@googlegroups.com> wrote:
Ohh
My problem is highly nonlinear with non linear constraints and nonlinear objective function. I tried to use other solvers but those didn't work. E.g. Knitro gave me an error that it can't handle non linear quadratic constraint. I also try using SNOPT (i hope i spelled it right) which doesn't seems better than MINOS. Other than that I tried different other solver which are not able to solve it. Can you suggest some solver.Even with MINOS sometimes it says infeasible problem or bad starting guess. I have been trying to reduce my problem size as small as possible and trying various ways.
Please suggest something in this regard.
Thanks
Harprinder
On Tue, Jul 2, 2019 at 10:41 AM UTC, AMPL Google Group <am...@googlegroups.com> wrote:
MINOS has given the termination message "the objective has not changed for the last 358 iterations." This means that MINOS has become stuck at a solution that does not satisfy the local optimality conditions.
Thus MINOS is unable to solve the problem from the given starting point. A carefully chosen starting point may give better results; see the discussion at https://ampl.com/BOOK/CHAPTERS/21-nonlinear.pdf#page=8. (Note that if you do not specify any starting point, a start with all variables at zero is assumed; for many problems, this is not a good choice.)
Also you may want to try other nonlinear solvers. In particular, the algorithm implemented in MINOS is best for problems that have a lot of linear or near-linear constraints, while other solvers may do better on problems that mostly have highly nonlinear constraints.
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Robert Fourer
am...@googlegroups.com