Why fmincon's interior-point algorithm gives infeasible points for feasibility problem?
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I am creating an initial feasible population for my optimization problem along the lines of this. I tried the technique with different solvers included in fmincon and noticed that albeit slowly, the medium-scale solvers sqp and active-set could give me feasible points but some points returned by the large-scale interior-point did not satisfy the constraints. Why this happens?
My problem has about 2000 linear inequality constraints and about 1500 variables, where none of them are integers.
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Sean de Wolski
2019 年 4 月 29 日
編集済み: Sean de Wolski
2019 年 4 月 29 日
Post the MAT file containing the constraints and the code you use to optimize. IP should not be returning infeasible points and it is likely a bug in your constraints.
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