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Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints
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Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints

Chettha Chamnanlor, Kanchana Sethanan, Mitsuo GenChen-Fu Chien
Journal of Intelligent Manufacturing
24/04/2015

摘要

Ant colony optimization Hybrid genetic algorithm Local search Reentrant flexible flow shop Time window
This paper focuses on minimizing the makespan for a reentrant hybrid flow shop scheduling problem with time window constraints (RHFSTW), which is often found in manufacturing systems producing the slider part of hard-disk drive products, in which production needs to be monitored to ensure high quality. For this reason, production time control is required from the starting-time-window stage to the ending-time-window stage. Because of the complexity of the RHFSTW problem, in this paper, genetic algorithm hybridized ant colony optimization (GACO) is proposed to be used as a support tool for scheduling. The results show that the GACO can solve problems optimally with reasonable computational effort.

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