A reinforcement learning-driven brain storm optimisation algorithm for multi-objective energy-efficient distributed assembly no-wait flow shop scheduling problem

A reinforcement learning-driven brain storm optimisation idea (RLBSO) is proposed in this paper to solve multi-objective energy-efficient distributed assembly no-wait flow shop scheduling problem. The objectives of the problem include minimising the maximum assembly completion time ( ), minimising t...

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Vydané v:	International journal of production research Ročník 61; číslo 9; s. 2854 - 2872
Hlavní autori:	Zhao, Fuqing, Hu, Xiaotong, Wang, Ling, Xu, Tianpeng, Zhu, Ningning, Jonrinaldi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Taylor & Francis 03.05.2023 Taylor & Francis LLC
Predmet:	Algorithms Assembly brain storm optimisation Clustering clustering mechanism Completion time Critical path Energy consumption Energy-efficient Factories Industrial plants Job shop scheduling Multiple objective analysis no-wait flow shop Optimization product assignment rule Q-learning mechanism Resource allocation
ISSN:	0020-7543, 1366-588X
On-line prístup:	Získať plný text
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