A multiobjective memetic algorithm with particle swarm optimization and Q-learning-based local search for energy-efficient distributed heterogeneous hybrid flow-shop scheduling problem

Most existing distributed hybrid flow-shop scheduling problems (DHFSPs) assume identical shops and lack consideration of heterogeneous shops. This study focuses on energy-efficient heterogeneous DHFSP. A multiobjective memetic algorithm with particle swarm optimization and Q-learning-based local sea...

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Vydané v:	Expert systems with applications Ročník 237; s. 121570
Hlavní autori:	Zhang, Wenqiang, Li, Chen, Gen, Mitsuo, Yang, Weidong, Zhang, Guohui
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.03.2024
Predmet:	Energy-efficient Heterogeneous distributed scheduling Hybrid flow-shop scheduling Memetic algorithm Particle swarm optimization Q-learning Memetic algorithm Q-learning Energy-efficient Particle swarm optimization Hybrid flow-shop scheduling Heterogeneous distributed scheduling
ISSN:	0957-4174, 1873-6793
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