Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/42245
Título: A biased-randomised large neighbourhood search for the two-dimensional vehicle routing problem with Backhauls
Autores/as: Dominguez, Oscar
Guimarans, Daniel
Juan, Angel A.
Nuez Pestana, Ignacio de la 
Clasificación UNESCO: 33 Ciencias tecnológicas
Palabras clave: Metaheuristics
Packing
Routing
Transportation
Vehicle routing problem
Fecha de publicación: 2016
Publicación seriada: European Journal of Operational Research 
Resumen: The two-dimensional loading vehicle routing problem with clustered backhauls (2L-VRPB) is a realistic extension of the classical vehicle routing problem where both delivery and pickup demands are composed of non-stackable items. Despite the fact that the 2L-VRPB can be frequently found in real-life transportation activities, it has not been analysed so far in the literature. This paper presents a hybrid algorithm that integrates biased-randomised versions of vehicle routing and packing heuristics within a Large Neighbourhood Search metaheuristic framework. The use of biased randomisation techniques allows to better guide the local search process. The proposed approach for solving the 2L-VRPB is tested on an extensive set of instances, which have been adapted from existing benchmarks for the two-dimensional loading vehicle routing problem (2L-VRP). Additionally, when no backhauls are considered our algorithm is able to find new best solutions for several 2L-VRP benchmark instances with sequential oriented loading, both with and without items rotation.
URI: http://hdl.handle.net/10553/42245
ISSN: 0377-2217
DOI: 10.1016/j.ejor.2016.05.002
Fuente: European Journal of Operational Research [ISSN 0377-2217], v. 255 (2), p. 442-462
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