Learnheuristics : Hybridizing metaheuristics with machine learning for optimization with dynamic inputs
Calvet Liñan, Laura (Universitat Oberta de Catalunya)
Armas, Jésica De (Universitat Oberta de Catalunya)
Masip, David (Universitat Oberta de Catalunya)
Juan, Ángel A (Universitat Oberta de Catalunya)

Date:	2017
Abstract:	This paper reviews the existing literature on the combination of metaheuristics with machine learning methods and then introduces the concept of learnheuristics, a novel type of hybrid algorithms. Learnheuristics can be used to solve combinatorial optimization problems with dynamic inputs (COPDIs). In these COPDIs, the problem inputs (elements either located in the objective function or in the constraints set) are not fixed in advance as usual. On the contrary, they might vary in a predictable (non-random) way as the solution is partially built according to some heuristic-based iterative process. For instance, a consumer's willingness to spend on a specific product might change as the availability of this product decreases and its price rises. Thus, these inputs might take different values depending on the current solution configuration. These variations in the inputs might require from a coordination between the learning mechanism and the metaheuristic algorithm: at each iteration, the learning method updates the inputs model used by the metaheuristic.
Grants:	Ministerio de Economía y Competitividad TRA2013-48180-C3-P Ministerio de Economía y Competitividad DPI2013-44461-P Ministerio de Economía y Competitividad TIN2015-66951-C2-2-R Generalitat de Catalunya 2014/CTP-00001
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article de revisió ; recerca ; Versió publicada
Subject:	Combinatorial optimization ; Dynamic inputs ; Hybrid algorithms ; Machine learning ; Metaheuristics
Published in:	Open Mathematics, Vol. 15, Issue 1 (March 2017) , p. 261-280, ISSN 2391-5455

DOI: 10.1515/math-2017-0029

20 p, 636.8 KB

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