关键词: 半自动存储检索系统, 多路径混合式, 遗传算法, 大规模邻域搜索算法

Abstract: Focusing on the practical scheduling scenario of a single workstation task scheduling problem of “carton-transfer-unit” warehouse system under multi-path hybrid environments, this paper investigates a special  multi-trip mixed return vehicle routing problem. First, considering a hybrid path mode that includes both open and closed routes, it proposes an integer linear programming model to minimize the maximum completion time of mixed outbound and inbound tasks for robots. Next, based on the pick-and-place characteristics of robots performing, it integrates the population management mechanism of genetic algorithms to improve the adaptive large neighborhood search process, aiming to avoid premature convergence to local optima while balancing the trade-off between the convergence speed of neighborhood search and population diversity. Finally, the proposed model and method are numerically validated by simulations and comparative analysis using test instances of various scales. Experimental results against several baseline methods demonstrate that the proposed algorithm significantly improves convergence, stability, and convergence speed. The findings provide methodological reference and decision support for robot task scheduling in single-workstation settings in “carton-transfer-unit” warehouse systems.

Key words: semi-automatic storage and retrieval system, multi-path hybrid, genetic algorithm, large neighborhood search algorithm