Web: http://arxiv.org/abs/2110.02121

Sept. 23, 2022, 1:12 a.m. | Adejuyigbe Fajemisin, Donato Maragno, Dick den Hertog

cs.LG updates on arXiv.org arxiv.org

Many real-life optimization problems frequently contain one or more
constraints or objectives for which there are no explicit formulas. If data is
however available, these data can be used to learn the constraints. The
benefits of this approach are clearly seen, however there is a need for this
process to be carried out in a structured manner. This paper therefore provides
a framework for Optimization with Constraint Learning (OCL) which we believe
will help to formalize and direct the process …

arxiv framework optimization survey

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