A Hyper-Heuristic Based on An Adapter Layer for Transportation Combinatorial Problems

Enrique Urra, CLAUDIO ALONSO CUBILLOS FIGUEROA, Daniel Cabrera Paniagua

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

1 Cita (Scopus)

Resumen

Hyper-heuristics are optimization techniques for solving hard combinatorial problems. Their main feature is that their design involves an important decoupling of the search components from the problem domain ones. This allows them to extend their applicability to different problem domains without major redesign, unlike traditional methods such as metaheuristics. In this work, a hyper-heuristic is evaluated for a transportation problem. The implemented hyper-heuristic uses a greedy operator, and it implements an adapter layer that would allow it to be used in other similar problems. Experimental results shows balanced solution quality and CPU time performance, regarding other metaheuristics in literature.

Idioma originalInglés
Número de artículo7555251
Páginas (desde-hasta)2764-2769
Número de páginas6
PublicaciónIEEE Latin America Transactions
Volumen14
N.º6
DOI
EstadoPublicada - jun 2016
Publicado de forma externa

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