Integrated optimization of automated guided vehicles and yard cranes considering charging constraints

AbstractTo improve the operational efficiency of automated container terminals and the coordination between multiple operations, this article studies the integrated scheduling optimization problem of automated guided vehicles (AGVs) and yard cranes. The impact of charging constraints on AGV task allocation and scheduling is considered. With the goal of minimizing the maximum completion time of all tasks, a mixed integer programming model is proposed. A solution method based on a dynamic programming algorithm is designed, where a heuristic algorithm is used to assign tasks to the yard cranes, and the dynamic programming method is used to assign tasks to the AGVs based on the task assignment results of the yard cranes. Finally, the validity of the model and algorithm is tested by numerical experiments. Furthermore, the influence of the quantity of AGVs on the terminal operational efficiency and the impact of AGV charging strategies on AGV scheduling are analysed.KEYWORDS: Automated container terminalAGVintegrated schedulingcharging constraints AcknowledgementsThe authors would like to express their sincere gratitude to the editors and reviewers for their time and effort in reviewing this article. The suggestions were very valuable and improved this work significantly.Data availability statementThe data that support the findings of this article are available upon request from the corresponding author.Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThis article is supported by the National Natural Science Foundation of China [grant number 71901005] and the Social Science Program of Beijing Municipal Education Commission [grant number SM202010011008]. The article is also supported by China Scholarship Council.