Learning to handle parameter perturbations in Combinatorial Optimization: An application to facility location
EURO Journal on Transportation and Logistics(2020)
摘要
We present an approach to couple the resolution of Combinatorial Optimization problems with methods from Machine Learning. Specifically, our study is framed in the context where a reference discrete optimization problem is given and there exist data for many variations of such reference problem (historical or simulated) along with their optimal solution. Those variations can be originated by disruption but this is not necessarily the case. We study how one can exploit these to make predictions about an unseen new variation of the reference instance.
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关键词
Mathematical programming,Machine learning,Recurrent problems
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