Journal
FUZZY SETS AND SYSTEMS
Volume 278, Issue -, Pages 81-97Publisher
ELSEVIER
DOI: 10.1016/j.fss.2014.12.003
Keywords
Flexible job shop scheduling; Robustness; Local search; Coevolutionary algorithm; Ranking of fuzzy numbers; Fuzzy processing
Funding
- Spanish Government [TIN2013-46511-C2-2-P, FEDER TIN2010-20976-C02-02, MTM2010-16051]
- Principality of Asturias Government under FICYT Grants [FC-13-COF13-035, BP13106]
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In this paper we tackle a variant of the flexible job shop scheduling problem with uncertain task durations modelled as fuzzy numbers, the fuzzy flexible job shop scheduling problem or FfJSP in short. To minimise the schedule's fuzzy makespan, we consider different ranking methods for fuzzy numbers. We then propose a cooperative coevolutionary algorithm with two different populations evolving the two components of a solution: machine assignment and task relative order. Additionally, we incorporate a specific local search method for each population. The resulting hybrid algorithm is then evaluated on existing benchmark instances, comparing favourably with the state-of-the-art methods. The experimental results also serve to analyse the influence in the robustness of the resulting schedules of the chosen ranking method. (C) 2014 Elsevier B.V. All rights reserved.
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