Multi-objective evolutionary algorithm based on multiple neighborhoods local search for multi-objective distributed hybrid flow shop scheduling problem

•A multi-objective distributed hybrid flow shop scheduling problem is studied.•A MOEA-LS is presented for solving the MDHFSP.•Several multiple neighborhoods local search operators are designed.•An adaptive weight updating mechanism is utilized to update weight set.•The MOEA-LS obtains better results...

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Veröffentlicht in:	Expert systems with applications Jg. 183; S. 115453
Hauptverfasser:	Shao, Weishi, Shao, Zhongshi, Pi, Dechang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 30.11.2021 Elsevier BV
Schlagworte:	Business competition Earliness and tardiness Evolutionary algorithms Factories Genetic algorithms Industrial plants Job shop scheduling Job shops Makespan Multi-objective distributed hybrid flow shop scheduling problem Multiple neighborhoods local search Multiple objective analysis Neighborhoods Optimization Searching Simulated annealing Workload Multiple neighborhoods local search Makespan Multi-objective distributed hybrid flow shop scheduling problem Workload Earliness and tardiness
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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