一种多巷道立体仓库货位分配优化方法

An Optimization Method of Cargo Space Allocation in Multi-tunnel Stereoscopic Warehouse

针对多巷道立体仓库货位分配问题,建立了以货物出入库效率、货架整体稳定性、堆垛机负载均衡为优化目标的多目标优化模型。针对该模型提出了一种自适应多种群遗传算法(AMPGA),引入余弦型自适应遗传算子实现种群中个体的交叉率和变异率动态自适应调整,同时对每个种群采用不同的交叉策略,并通过引入具有单方向性的进化逆转算子来克服其存在的局部搜索能力差和早熟收敛等问题,使之跳出局部最优,保持全局搜索能力。不同订单规模下的实验结果表明,MPGA相比于SGA优化提高2%~12%,AMPGA相比于SGA优化提高2%~14%,且AMPGA优化程度比MPGA更显著,耗时更短,对于货位优化结果更合理,是一种解决多巷道立体仓库货位分配优化的有效方法。

In order to solve the problem of space allocation in multi-tunnel warehouse,a mathematical model of space allocation optimization is established with the efficiency of goods in and out of warehouse,overall stability of shelf and load balance of stacker as the optimization objectives.An adaptive multi population genetic algorithm(AMPGA)is proposed for this model.The cosine adaptive genetic operator is introduced to realize the dynamic adaptive adjustment of the crossover rate and mutation rate of individuals in the population.At the same time,different crossover strategies are adopted for each population.The unidirectional evolutionary inversion operator is introduced to overcome the problems of poor local search ability and premature convergence,so that it can jump out of the local optimum and maintain the global search ability.The experimental results under different order sizes show that MPGA is 2%~12%higher than SGA optimization,AMPGA is 2%~14%higher than SGA optimization,and AMPGA optimization is more significant than MPGA,with less time consumption.It is more reasonable for the results of location optimization,and is an effective method to solve the location allocation optimization of multi-tunnel stereoscopic warehouse.