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The rear warehouse picking path is an important part of the warehouse business work, which directly affects the efficiency of the warehouse business. Aiming at the problem of picking path optimization in the rear warehouse of the current army, to improve the picking efficiency of the warehouse, aiming at the shortest picking time, the objective function model of the picking path optimization problem is constructed for the composite operation mode of the rear warehouse, and a hybrid solution algorithm combining traditional particle swarm optimization ( PSO ) and genetic algorithm ( GA ) is proposed. Through 20 times of simulation analysis with examples, it is shown that the standard deviation of the running time of the hybrid algorithm is 0.87 seconds, the mean value is 37.89 seconds, and the average optimization rate is 41.52 %. Compared with the traditional PSO algorithm, the optimization results of the hybrid algorithm are better than those of the PSO algorithm in all aspects. The simulation results show that the PSO-GA algorithm has certain advantages, which can effectively reduce the operation time of the warehouse picking operation and improve the efficiency of the warehouse operation. It has certain theoretical value and practical significance for the optimization of the picking path of the rear warehouse.

Research on Optimization of Picking Path in Rear Warehouse Oriented to Mixed Operation Mode