面向低能耗的密集仓储货位分配优化

Optimization of storage location assignment in compact storage and retrieval system for low energy consumption

针对四向车式密集仓储系统的货位分配问题,提出一种四向车及提升机的能耗计算模型,并考虑动态货位可行域约束等因素,建立了以减少能耗为主要目标且兼顾降低货架重心与作业分布均衡的货位分配优化模型。设计自适应变异的差分进化算法对模型进行求解,向量个体表示单批作业的目标货位集合,将个体基因位的值域映射为相应出入库作业的货位可行域,根据此动态货位可行域进行个体解码后得出可行货位解,通过综合评价个体的优劣及种群迭代进化获得作业的最优货位解。在3种预设库存和3种载荷类型的情况下分别进行试验,结果表明,与考虑最短距离的货位分配优化模型相比,所提出的模型及算法可有效降低仓储能耗且其性能优势明显。

Aiming at the optimization problem of storage location assignment in four-way shuttle compact storage and retrieval system,an energy consumption calculation model for four-way shuttle and elevator was proposed.Considering the constraints of the dynamic available storage location domain and other factors,an optimization model of storage location allocation was established to decrease energy consumption,lower gravity center of shelf and balance operation allocation.A differential evolution algorithm of adaptive mutation operator was designed.The individual represented the target storage location solution for a single batch of operations.The individual was decoded according to the dynamic storage location domain which was mapped from the value range of each gene.Through comprehensive evaluation of individual,the optimal storage location solution was obtained with population iterative evolution.A number of experiments were conducted under the conditions of three kinds of inventory and three types of goods.The results show that compared with the location optimization model considering the shortest distance,the proposed optimization model and algorithm have significant advantages in energy consumption reduction and solution efficiency.can effectively reduce the energy consumption of storage and its performance advantages are abvious.