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To solve linear or quadratic programming problems in python, we often resort to scipy.optimize.minimize, which provides a heuristic platform to design optimization problems.

Could anyone refer me to examples of polynomial goal programming (PGP) in python? PGP is used to solve multi-objective non-convex optimization problems. To start, any scientific problem will do.

develarist
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  • *To solve linear or quadratic programming problems in python, we often resort to scipy.optimize.minimize* I have never encountered serious LP/QP applications using this, only student projects. – Erwin Kalvelagen Nov 03 '20 at 12:48
  • @ErwinKalvelagen do you know any example links that apply PGP in python? – develarist Nov 03 '20 at 12:49
  • No. Usually, we use piecewise linear formulations. This allows us to use off-the-shelf high-performance solvers. In practice, we don't need to use a precise polynomial function form to penalize the deviations as these typically have no direct physical meaning. So a piecewise linear formulation with just a few segments was always more than adequate in applications I was involved with. – Erwin Kalvelagen Nov 03 '20 at 12:57
  • the question is not whether PGP is adequate or student material, it's are there any python codes out there that conduct PGP (so i can see how they run) – develarist Nov 03 '20 at 13:41

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