关键词: 密集仓储, 货位分配, 混合蛙跳算法, 遗传算法

Abstract: Aiming at the problems of the dense distribution and the dynamic changes of cargo spaces in the location allocation of four-way shuttle storage and retrieval system, a multi-objective cargo space allocation method aiming at improving warehouse work efficiency and equipment stability is established, and a new method is proposed. An improved shuffled frog leading algorithm is proposed to simulate and optimize the model. First of all, according to the distribution characteristics of cargo spaces in intensive warehousing, a strategy of cargo space and cargo lanes is proposed, and a cargo space allocation principle for goods stored in cargo lanes by category is established. Then, a mathematical model of cargo space allocation is established with the goal of shortest path, balanced distribution of goods and lower center of shelves gravity. Finally, an improved shuffled frog leading algorithm is proposed to solve the model by using dynamic adaptive crossover to improve the local search strategy of the standard shuffled frog leading algorithm. The simulation results show that the cargo space allocation model is reasonable, and compared with the standard genetic algorithm and the standard shuffled frog leading algorithm, the improved shuffled frog leading algorithm has faster convergence speed, more reasonable optimization of cargo space, and can effectively solve the problem of location allocation of four-way shuttle storage and retrieval system.

Key words: dense storage, location allocation, shuffles frog leaping algorithm, genetic algorithm