Hybrid cooperative coevolution for fuzzy flexible job shop scheduling problems
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Universidad de Oviedo
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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
Patrocinado por:
FEDER TIN2010-20976-C02-02 y MTM2010-16051
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