Can mystic optimizer be used to minimize a non-convex Mixed Integer Non-Linear Programming problem with only integer inputs?Because,the objective function is not continuous in x(the input),it is discretized in integers.
Mystic for non-convex MINLP
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I'm the
mystic
author... yes. Mystic can handle non-convex problems, with the Differential Evolution solver, or one of the Ensemble solvers. There is no MLP-specific solver, but instead handles integer programming as a spatial map that constrains solution space -- either passnp.round
to the solver as a constraint, or use theintegers
decorator on a constraint.For example, see:
Updated to respond to comments below To provide another example of constraints... if you want to impose a sum on the square of inputs, you could do it like this:
mystic
has several modules where you can find pre-built constraints functions, but the best places to start are:mystic.constraints
andmystic.tools
for general constraints,mystic.math.measures
for statistical constraints,mystic.symbolic
for symbolic constraints, andmystic.penalty
for soft constraints (i.e. penalties).