Abstract: Addressing the problems of stacker crane load imbalance and low storage/retrieval efficiency in multi-aisle automated storage and retrieval systems under dynamic operating conditions,this paper aims to construct an integrated optimization model for storage location assignment and job scheduling that considers load balancing to enhance overall warehouse operational efficiency.Firstly,soft set theory is employed to partition the shelves,and a parameterized classification mechanism is used to divide goods into regions based on their characteristic attributes and demand,effectively reducing the search space for storage locations.Secondly,a two-stage mathematical model is developed for integrated optimization of stacker crane load balancing and job scheduling.Subsequently,an improved sparrow search algorithm suitable for discrete sequencing problems is designed.Simulation expe-riments demonstrate that the optimized sparrow search algorithm outperforms the comparison algorithms across different instruction scales.The load balancing model effectively improves the uniformity of the stacker crane operation time distribution,enhancing the overall optimization results.The proposed method exhibits excellent performance in terms of optimization efficiency,convergence speed,and robustness.

Key words: Multi-aisle automated storage and retrieval system, Sparrow search algorithm, Load balancing, Storage location assignment, Job scheduling, Integrated optimization, Soft set theory