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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Bibliographic Details
Published in:	International journal of production research Vol. 61; no. 9; pp. 2854 - 2872
Main Authors:	Zhao, Fuqing, Hu, Xiaotong, Wang, Ling, Xu, Tianpeng, Zhu, Ningning, Jonrinaldi
Format:	Journal Article
Language:	English
Published:	London Taylor & Francis 03.05.2023 Taylor & Francis LLC
Subjects:	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
Online Access:	Get full text
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