Reinforcement Learning-Based Multiobjective Evolutionary Algorithm for Mixed-Model Multimanned Assembly Line Balancing Under Uncertain Demand

In practical assembly enterprises, customization and rush orders lead to an uncertain demand environment. This situation requires managers and researchers to configure an assembly line that increases production efficiency and robustness. Hence, this work addresses cost-oriented mixed-model multimann...

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Veröffentlicht in:	IEEE transactions on cybernetics Jg. 54; H. 5; S. 1 - 14
Hauptverfasser:	Zhang, Zikai, Tang, Qiuhua, Chica, Manuel, Li, Zixiang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.05.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Assembly line balancing (ALB) Assembly lines Balancing Costs Demand Evolutionary algorithms Genetic algorithms Idling Integer programming Job shop scheduling Linear programming Machine learning Mixed integer multimanned multiobjective optimization Multiple objective analysis Mutation Operators Optimization Production reinforcement learning (RL) Robustness Strategy Task analysis uncertain demand Workstations
ISSN:	2168-2267, 2168-2275, 2168-2275
Online-Zugang:	Volltext
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