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Multi-label Classification for the Generation of Sub-problems in Time-constrained Combinatorial Optimization

Mossina, Luca and Rachelson, Emmanuel and Delahaye, Daniel Multi-label Classification for the Generation of Sub-problems in Time-constrained Combinatorial Optimization. (2019) In: 8th International Conference on Operations Research and Enterprise Systems (ICORES 2019), 19 February 2019 - 21 February 2019 (Prague, Czech Republic).

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Abstract

his paper addresses the resolution of combinatorial optimization problems presenting some kind of recurrent structure, coupled with machine learning techniques. Stemming from the assumption that such recurrent problems are the realization of an unknown generative probabilistic model, data is collected from previous resolutions of such problems and used to train a supervised learning model for multi-label classification. This model is exploited to predict a subset of decision variables to be set heuristically to a certain reference value, thus becoming fixed parameters in the original problem. The remaining variables then form a smaller sub-problem whose solution, while not guaranteed to be optimal for the original problem, can be obtained faster, offering an advantageous tool for tackling time-sensitive tasks.

Item Type:Conference or Workshop Item (Paper)
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Ecole Nationale de l'Aviation Civile - ENAC (FRANCE)
Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
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Deposited By: Luca Mossina
Deposited On:09 Apr 2019 14:32

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