Real-time production scheduling using a deep reinforcement learning-based multi-agent approach

IF 1.1 4区计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

Infor Pub Date : 2024-03-03 DOI:10.1080/03155986.2023.2287996

Sharareh Taghipour, Hamed A. Namoura, Mani Sharifi, Mageed Ghaleb

引用次数: 0

Abstract

In the real-time scheduling (RTS) research field, it has been shown that employing multiple dispatching rules (MDRs) for the components in a flexible manufacturing system will improve production pe...

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使用基于深度强化学习的多代理方法进行实时生产调度

在实时调度（RTS）研究领域，有研究表明，在柔性制造系统中对部件采用多重调度规则（MDR）将提高生产效率，并降低生产成本。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Infor 管理科学-计算机：信息系统

CiteScore

2.60

自引率

7.70%

发文量

审稿时长

>12 weeks

期刊介绍： INFOR: Information Systems and Operational Research is published and sponsored by the Canadian Operational Research Society. It provides its readers with papers on a powerful combination of subjects: Information Systems and Operational Research. The importance of combining IS and OR in one journal is that both aim to expand quantitative scientific approaches to management. With this integration, the theory, methodology, and practice of OR and IS are thoroughly examined. INFOR is available in print and online.