Job scheduling optimization in autonomous vehicle storage and retrieval system with multi-level rack based on a hybrid heuristic algorithm

The autonomous vehicle storage and retrieval system (AVS/RS) with multi-level rack has good application prospects due to its excellent throughput capacity and flexibility. This paper presents a mathematical model of inbound and outbound job’s scheduling problem in AVS/RS with multilevel rack based on the parallel work of lift, vehicles and telescopic arms, and the optimization objective is to minimize the makespan. This paper proposes a novel hybrid heuristic algorithm based on Harris Hawk Optimization (HHO) and Adaptive Large Neighborhood Search (ALNS) to solve the optimization problem. The study conducts numerical experiments to verify the effectiveness of the proposed algorithm. For small-scale problems, the mathematical model is solved by the Gurobi, and the results show that the proposed algorithm can obtain a solution with an average deviation of less than 3% from the exact solution in a short time. For medium-scale and large-scale problems, the proposed algorithm is more efficient and stable compared to other heuristics. This research has practical implications for optimizing the sequence of operations and improving the work efficiency of AVS/RS with multi-level rack.