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Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/11012

Title: Fast local search for fuzzy job shop scheduling
Author(s): Puente Peinador, Jorge
Rodríguez Vela, María del Camino
González Rodríguez, Inés
Issue date: 2010
Publisher: IOS Press
Publisher version: http://dx.doi.org/10.3233/978-1-60750-606-5-739
Citation: Frontiers in Artificial Intelligence and Applications, 215, p. 739-744 (2010); doi:10.3233/978-1-60750-606-5-739
Format extent: p. 739-744
Abstract: In the sequel, we propose a new neighbourhood structure for local search for the fuzzy job shop scheduling problem. This is a variant of the well-known job shop problem, with uncertainty in task durations modelled using fuzzy numbers and where the goal is to minimise the expected makespan of the resulting schedule. The new neighbourhood structure is based in changing the relative order of subsequences of tasks within critical blocks. We study its theoretical properties and provide a makespan estimate which allows to select only feasible neighbours while covering a greater portion of the search space than a previous neighbourhood from the literature. Despite its larger search domain, experimental results show that this new structure notably reduces the computational load of local search with respect to the previous neighbourhood while maintaining or even improving solution quality
Description: ECAI 2010
URI: http://hdl.handle.net/10651/11012
ISSN: 0922-6389
Local identifier: 20101025
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