Simulation-based regression analysis for the replenishment strategy of the crane & shuttle-based storage and retrieval system

• Published in: Cluster computing Vol. 25; no. 1; pp. 77 - 89
• Main Authors: Ma, Wenkai, Hu, Jinchang, Wang, Yanyan, Wu, Yaohua
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2022; Springer Nature B.V
• Subjects: Automation; Computer Communication Networks; Computer Science; Consumer goods; Cranes; Cranes & hoists; Data analysis; Design optimization; Efficiency; Energy consumption; Operating Systems; Order picking; Processor Architectures; Queuing; Regression analysis; Replenishment; Retrieval; Robotics; Shuttles; Simulation; Simulation models; Statistical analysis; Supply chains; Systems analysis; United States > US; Order structure; Automatic warehouse sorting system; Big data analysis; Replenishment
• ISSN: 1386-7857; 1573-7543
• DOI: 10.1007/s10586-021-03372-7

This research focuses on big experimental data analysis and the replenishment operation in a crane & shuttle based storage and retrieval system (C&SBS/RS). It is proposed that the order structure is expressed by three indicators: the order strength, the order size, and the order density. This aims to develop a regression function for the replenishment strategy to reveal the relationship between the order structure and replenishment parameters. The simulation model of the system is developed using FlexSim 7.1. A total of 13,440 combinations of order structures are provided as the simulation input. The statistical analyses are completed using the popular statistical software MINITAB. In this study, we use two different methods, best subset regression, and stepwise regression, to fit the regression function and find the best regression. According to the regression function, operation managers can develop better operation strategies.