Selection and generation hyper-heuristics for solving the vehicle routing problem with time windows

David Espinoza-Nevárez, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Gustavo Gatica

Resultado de la investigación: Contribución a los tipos de informe/libroContribución a la conferencia

2 Citas (Scopus)

Resumen

The vehicle routing problem is a classic optimization problem with many variants. One of the variants is given by the inclusion of the time windows constraint which requires the clients to be served within a delimited time frame. Because of its complexity, vehicle routing problems are usually solved by using heuristics without optimality guarantee. This paper describes two hyper-heuristics capable of producing results comparable to the ones obtained by the best-performing heuristics on different sets of benchmark instances.

Idioma originalInglés
Título de la publicación alojadaGECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference
EditorialAssociation for Computing Machinery, Inc
Páginas139-140
Número de páginas2
ISBN (versión digital)9781450343237
DOI
EstadoPublicada - 20 jul 2016
Evento2016 Genetic and Evolutionary Computation Conference, GECCO 2016 Companion - Denver, Estados Unidos
Duración: 20 jul 201624 jul 2016

Otros

Otros2016 Genetic and Evolutionary Computation Conference, GECCO 2016 Companion
PaísEstados Unidos
CiudadDenver
Período20/07/1624/07/16

Áreas temáticas de ASJC Scopus

  • Software
  • Informática aplicada
  • Teoría computacional y matemáticas

Huella Profundice en los temas de investigación de 'Selection and generation hyper-heuristics for solving the vehicle routing problem with time windows'. En conjunto forman una huella única.

  • Citar esto

    Espinoza-Nevárez, D., Ortiz-Bayliss, J. C., Terashima-Marín, H., & Gatica, G. (2016). Selection and generation hyper-heuristics for solving the vehicle routing problem with time windows. En GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference (pp. 139-140). Association for Computing Machinery, Inc. https://doi.org/10.1145/2908961.2909051