具有双命令事务的紧凑型存取系统的机器人调度问题

IF 2.2 3区工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY

Engineering Optimization Pub Date : 2023-11-13 DOI:10.1080/0305215x.2023.2269849

Dongjun Cai, Xi Xiang, Loo Hay Lee, Ek Peng Chew, Kok Choon Tan

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引用次数: 0

摘要

摘要机器人紧凑型存储检索系统(RCSRS)是一种基于网格的系统，近年来在世界各地的在线零售商中得到了广泛的应用。本文研究了RCSRS的机器人调度问题，旨在减少机器人空行时间和工作站空闲时间。机器人调度问题是在给定工作站任务序列的情况下，将任务分配给机器人。此外，机器人在此问题中遵循快速的双命令处理过程。因此，为优化系统性能，提出了一种适合双命令事务处理的混合整数规划模型。在此基础上，提出了一种基于ε-贪心算法的自适应邻域搜索算法。实验结果表明，与实践中使用的各种算法和相关文献中讨论的算法相比，作者所提出的算法具有优越性。此外，还为生成的实例提出了最佳系统配置建议。关键词:紧凑型存储系统机器人调度双命令自适应邻域搜索感谢蔡东军感谢他的工业主管吴庆孟博士，他为开展这项工作提供了支持性建议和所需的资源。他们亦非常感谢他们的导师及导师，已故的卢海教授，在整个研究过程中给予他们耐心的指导、建议和鼓励。披露声明作者未报告潜在的利益冲突。数据可用性声明作者确认在文章中可以获得支持本研究结果的数据。本研究没有创建或分析新的数据。奚祥受国家自然科学基金资助[批准号:72301029]。蔡东军是新一代港口建模与仿真卓越研究中心的资助对象[批准号:3030012222341]。

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Robot dispatching problem for compact storage and retrieval systems with dual-command transactions

AbstractA robotic compact storage and retrieval system (RCSRS) is a grid-based system that has been popularly implemented by online retailers around the world recently. This article addresses a robot dispatching problem for RCSRS, aiming to reduce robot empty travelling time and workstation idle time. The robot dispatching problem is to assign tasks to robots when the task sequences in workstations are given. Additionally, the robots follow a fast dual-command transaction process in this problem. Hence, a mixed integer programming model catering for the dual-command transaction process is formulated to optimize system performance. Furthermore, an adaptive neighbourhood search with an ε-greedy algorithm is proposed to solve the problem. The experimental results substantiate the superiority of the authors' proposed algorithm compared to various algorithms used in practice and discussed in the relevant literature. Moreover, optimal system configurations for the instances generated are suggested.Keywords: Compact storage systemrobot dispatchingdual-commandadaptive neighbourhood search AcknowledgementsDongjun Cai thanks his industrial supervisor, Dr Ng Ging Meng, who provided supportive suggestions and the resources needed to carry out the work. They also express immense gratitude to their research supervisor and mentor, the late Professor Loo Hay Lee, for providing patient guidance, advice and encouragement throughout this study.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article. No new data were created or analysed in this study.Additional informationFundingXi Xiang is supported by the National Natural Science Foundation of China [Grant No. 72301029]. Dongjun Cai is supported by the funding of the Centre of Excellence in Modelling and Simulation for Next Generation Ports [Grant No. 3030012222341].

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来源期刊

Engineering Optimization 管理科学-工程：综合

CiteScore

5.90

自引率

7.40%

发文量

审稿时长

3.5 months

期刊介绍： Engineering Optimization is an interdisciplinary engineering journal which serves the large technical community concerned with quantitative computational methods of optimization, and their application to engineering planning, design, manufacture and operational processes. The policy of the journal treats optimization as any formalized numerical process for improvement. Algorithms for numerical optimization are therefore mainstream for the journal, but equally welcome are papers which use the methods of operations research, decision support, statistical decision theory, systems theory, logical inference, knowledge-based systems, artificial intelligence, information theory and processing, and all methods which can be used in the quantitative modelling of the decision-making process. Innovation in optimization is an essential attribute of all papers but engineering applicability is equally vital. Engineering Optimization aims to cover all disciplines within the engineering community though its main focus is in the areas of environmental, civil, mechanical, aerospace and manufacturing engineering. Papers on both research aspects and practical industrial implementations are welcomed.