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].