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Hybrid cooperative coevolution for fuzzy flexible job shop scheduling problems

Author:
Palacios Alonso, Juan JoséUniovi authority; Rodríguez Vela, María del CaminoUniovi authority; Puente Peinador, JorgeUniovi authority; González Rodríguez, InésUniovi authority
Publication date:
2013-12
Editorial:

Universidad de Oviedo

Descripción física:
p. 199-206
Abstract:

In this paper we consider a variant of the flexible job shop scheduling problem with uncertain task durations modelled as fuzzy numbers. We propose a cooperative coevolutionary algorithm to minimise the schedule’s makespan, with two different populations evolving the two main aspects that conform a solution: machine assignment and task relative order. Additionally, we incorporate a specific local search method for each population. The resulting hybrid algorithm, called CELS, is then evaluated on existing benchmark instances, comparing favourably with the state-ofthe-art methods

In this paper we consider a variant of the flexible job shop scheduling problem with uncertain task durations modelled as fuzzy numbers. We propose a cooperative coevolutionary algorithm to minimise the schedule’s makespan, with two different populations evolving the two main aspects that conform a solution: machine assignment and task relative order. Additionally, we incorporate a specific local search method for each population. The resulting hybrid algorithm, called CELS, is then evaluated on existing benchmark instances, comparing favourably with the state-ofthe-art methods

URI:
http://hdl.handle.net/10651/31980
Patrocinado por:

FEDER TIN2010-20976-C02-02 y MTM2010-16051

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