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Reinforcement Learning for Multi-Objective Multi-Echelon Supply Chain Optimisation

delete2026-02-10
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OA
AI
R
Rifny Rachman
J
Josh Tingey
R
Richard Allmendinger
P
Pradyumn Kumar Shukla
W
Wei Pan
DOI：10.1016/j.ejor.2026.02.002delete
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摘要

摘要

En 中文
• 开发了一个基于马尔可夫的多目标供应链优化模型。 • 引入了一个可定制的模拟器，用于动态供应链决策。 • 应用强化学习来平衡经济、环境和社交目标。 • 发现强化学习在目标之间实现了更好的权衡。 • 证明强化学习提高了运营的稳定性和平衡性。
Keyword:
Multiple objective programming
Markov processes
Supply chain optimisation
Reinforcement learning
Evolutionary algorithm
AI总结

AI总结

对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

European Journal of Operational Research 封面图
European Journal of Operational Research
IF:
6
论文数:
2.2W
被引数:
6.4W

机构

P
peak ai, ltd
学者数:
1
论文数: 1
被引数: 0
U
University of Manchester
学者数:
5.7W
论文数: 5.3W
被引数: 7.4W
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