六向穿梭机仓储系统多目标货位分配优化算法研究

Multi-Objective Storage Location Assignment Optimization Algorithm for Six-Way Shuttle Automated Storage and Retrieval Systems

摘要: 本文针对六向穿梭机仓储系统多目标货位分配优化算法进行研究。首先选择基于货物出入库效率原则、货架稳定性原则以及穿梭机作业均衡原则的随机存储策略作为仓库的存储方式，并建立六向穿梭机仓储入库货物货位分配数学模型；随后改进第三代快速非支配排序遗传算法(NSGA-III)进行模型求解，通过引入反向学习机制和随机扰动提高初始种群多样性，引入自适应差分变异平衡全局搜索和局部收敛能力。最后，结合实例进行仿真实验。通过与各个目标的单目标优化结果比较，验证构建模型的有效性和算法的实用性。

Abstract: This paper investigates the multi-objective storage location assignment optimization problem for six-way shuttle automated storage and retrieval systems. First, a random storage strategy is adopted as the storage method based on the principles of storage/retrieval efficiency, rack stability, and shuttle operation balance. Accordingly, a mathematical model of storage location assignment is established. We then enhanced the third-generation nondominated sorting genetic algorithm (NSGA-III) to solve the model. By embedding an opposition-based learning mechanism and random perturbation we boosted the diversity of the initial population, while an adaptive differential-mutation operator was introduced to balance global exploration and local convergence. Finally, a real-world instance was used for simulation experiments. Comparisons with single-objective optima of each target confirm the validity of the proposed model and the practicality of the algorithm.