Hybrid evolutionary approaches for the single machine order acceptance and scheduling problem.

Appl. Soft Comput.(2017)

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摘要
Graphical abstractDisplay Omitted HighlightsTwo evolutionary approaches are proposed for order acceptance and scheduling problem.First approach is based on steady-state genetic algorithm.Second approach is based on evolutionary algorithm with guided mutation.Our approaches are compared with two state-of-the-art approaches.Computational results show the effectiveness of our approaches. This paper presents two hybrid metaheuristic approaches, viz. a hybrid steady-state genetic algorithm (SSGA) and a hybrid evolutionary algorithm with guided mutation (EA/G) for order acceptance and scheduling (OAS) problem in a single machine environment where orders are supposed to have release dates and sequence dependent setup times are incurred in switching from one order to next in the schedule. OAS problem is an NP-hard problem. We have compared our approaches with the state-of-the-art approaches reported in the literature. Computational results show the effectiveness of our approaches.
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关键词
Steady-state genetic algorithm,Estimation of distribution algorithm,Evolutionary algorithm,Guided mutation,Order acceptance and scheduling,Single machine scheduling,Sequence dependent setup time
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