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Evolutionary tabu search for flexible due-date satisfaction in fuzzy job shop scheduling

Abstract: We consider the job shop scheduling problem with fuzzy sets modelling uncertain durations and flexible due dates. With the goal of maximising due-date satisfaction under uncertainty, we first give a new measure of overall due-date satisfaction in this setting. Then, we define a neighbourhood structure for local search, analyse its theoretical properties and provide a neighbour-estimation procedure. Additionally, a tabu search procedure using the neighbourhood is combined with a genetic algorithm, so the resulting memetic algorithm, guided by the defined due-date satisfaction measure, is run on a set of benchmarks. The obtained results illustrate the potential of our proposal.

Otras publicaciones de la misma revista o congreso con autores/as de la Universidad de Cantabria

 Fuente: Computers and Operations Research 119 (2020) 104931

Editorial: Elsevier

 Fecha de publicación: 01/07/2020

Nº de páginas: 16

Tipo de publicación: Artículo de Revista

 DOI: 10.1016/j.cor.2020.104931

ISSN: 0305-0548

Proyecto español: TIN2016-79190-R

Url de la publicación: https://doi.org/10.1016/j.cor.2020.104931

Autores/as

CAMINO RODRIGUEZ VELA

AFSAR, SEZIN

JUAN JOSE PALACIOS HOYOS

JORGE PUENTE PEINADOR