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
Sean de Wolski on 29 Apr 2019
Edited: Sean de Wolski on 29 Apr 2019
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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