Abstract: Aiming at the problem of storage allocation in two-way automatic warehouse,the mathematical model of cargo space allocation was established by taking the efficiency of product loading and unloading,the center of gravity of shelf and the degree of product aggregation as the goal.An improved shuffled frog leading algorithm was proposed to simulate and optimize the model.At the same time,a new local update strategy was designed while adopting this algorithm,in which a dynamic adaptive synchronization factor was introduced to make the algorithm jump out of the local optimum and maintain the global search capability.It offset the problem of slow convergence speed and easily falling into local optimal when solving complex problems.The simulation results showed that the improved leapfrog algorithm had less iteration,faster convergence speed by comparing with the standard genetic algorithm and the hybrid leapfrog algorithm,which was more reasonable to optimize the cargo space,and was an effective optimization method to solve the allocation of bidirectional warehouse space.

Key words: two-way automatic warehouse, storage allocation, shuffled frog leading algorithm, adaptive synchronization factor

摘要： 针对双向式自动化立体仓库货位分配问题,以产品出入库效率、货架重心和产品聚集度为目标建立了货位分配数学模型,提出一种改进混合蛙跳算法对模型进行仿真优化,同时采用该算法时设计了新的局部更新策略,引入动态自适应同步因子,使之跳出局部最优,保持全局搜索能力,弥补了其在解决复杂问题时收敛速度慢,易陷入局部最优的问题。实例仿真结果表明:与标准的遗传算法和混合蛙跳算法相比,改进后的蛙跳算法迭代次数更少,收敛速度更快,对货位的优化更加合理,是一种解决双向式立体仓库货位分配的有效优化方法。

关键词: 双向式立体仓库, 货位分配, 混合蛙跳算法, 自适应同步因子