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仓库拣选路径问题研究综述
引用本文:颜伟,孙佳旭,崔若梁.仓库拣选路径问题研究综述[J].科学技术与工程,2022,22(32):14081-14089.
作者姓名:颜伟  孙佳旭  崔若梁
作者单位:山东科技大学
基金项目:国家自然科学基金资助项目(51509149,51379119);国家重点研发计划资助项目(2018YFC0604702);山东省重点研发计划资助项目(2018GSF120009);青岛市哲学社会科学项目(QDSKL2001153)
摘    要:近年来,多品种、小批量的生产模式的盛行,给制造业的仓储带来了巨大的挑战,如何提高仓库的拣选效率是一个亟待解决的问题。因此,国内外学者针对仓库拣选路径问题提出了多种分类及研究方法。通过查阅相关文献,本文从两个角度对仓库拣选路径问题进行综述。首先,从拣选作业类型的角度,将研究问题分为单一作业和复合作业,分析仓库拣选路径问题的研究现状及存在的问题;其次,从研究方法的角度,将求解方法分为启发式算法和强化学习,分析近年来二者在仓库拣选路径问题中的应用;最后,对现有文献进行总结,并提出未来仓库拣选路径问题的发展方向。

关 键 词:仓库拣选路径问题  复合作业  单一作业  启发式算法  强化学习
收稿时间:2021/12/7 0:00:00
修稿时间:2022/8/5 0:00:00

Review on Warehouse Picking Path Problem
Yan Wei,Sun Jiaxu,Cui Ruoliang.Review on Warehouse Picking Path Problem[J].Science Technology and Engineering,2022,22(32):14081-14089.
Authors:Yan Wei  Sun Jiaxu  Cui Ruoliang
Institution:Shandong University of Science and Technology
Abstract:Recently, the prevalence of multi-variety and small-batch production mode has brought great challenges to the warehousing of the manufacturing industry. How to improve the efficiency of warehouse picking is an urgent problem to be solved. Therefore, domestic and foreign scholars have proposed a variety of classification and research methods for the problem of warehouse picking path. Through systematic review of relevant literature, this paper summarizes warehouse picking path problems from two perspectives. Firstly, from the perspective of picking operation types, the research problems are divided into single operation and compound operation, and the research status and existing problems of warehouse picking path problems are analyzed. Secondly, from the perspective of research methods, the solving methods are divided into heuristic algorithm and reinforcement learning, and the application of the two methods in warehouse picking path problem in recent years is analyzed. Finally, the existing literature is summarized, and the future development direction of warehouse selection path problem is proposed.
Keywords:Warehouse picking path problem      compound operations      Single operation  heuristic algorithm      reinforcement learning
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