关键词: 物流分拣搬运系统, 任务分配, 路径规划, 多目标鲸鱼优化算法, 改进A^*算法, 多目标双层仿真优化算法

Abstract: Regarding the collaborative optimization issue of task allocation at the sorting stations and path planning of AGVs in the logistics sorting and handling system, a problem model is established by taking the completion of sorting tasks and the response time of AGV tasks as the optimization objectives, a multi-objective two-level simulation optimization algorithm is designed for solution. The outer layer of this algorithm is the sorting station task allocation layer, and the inner layer is the AGV path planning layer. The sorting task allocation scheme obtained in the outer layer is regarded as the precondition for the operation of the inner layer for AGV path planning simulation. Based on the returned simulation results, the outer layer is optimized to achieve iterative optimization of the algorithm. At the outer layer of the algorithm, a multi-objective whale optimization algorithm is proposed. According to the problem characteristics, the whale optimization algorithm is discretely improved by introducing crossover and mutation, and a local search operator is constructed to enhance the local search ability of the algorithm. At the inner layer of the algorithm, an improved A^* algorithm is proposed. On the basis of the A^* algorithm, path load is introduced, and a cooling mechanism is adopted to achieve iterative update of the path load. Collaborative optimization is realized based on the correlated feedback between the inner and outer layers of the algorithm. Finally, the effectiveness and superiority of the proposed algorithm are verified through simulation experiments.

Key words: logistics sorting and handling system, task allocation, path planning, multi-objective whale algorithm, improved A^* algorithm, multi-objective two-level simulation optimization algorithm