摘要
近年来,以储销一体、批零兼营为主要特征的仓储式超市迅速兴起。该类仓储式超市有效地降低了仓储成本,但货品需要从存储货位不断搬运至销售货架上,造成了巨大的搬运工作量。为降低该类仓储式超市中的货品搬运工作量,考虑货架重心、同类货品聚集等约束条件,针对相应的存储货位指派问题建立了数学模型,并运用改进自适应交叉变异遗传算法进行求解。在算法设计上,采用了三种不同的邻域搜索算子来改进变异算子。数值实验表明,所提出的改进自适应交叉变异遗传算法的求解效果优于贪婪算法与一般遗传算法。算法结果也可以获得更短的搬运时间和更集中的货物摆放。最后通过关键参数对目标函数的影响分析发现,在同一问题规模下,存储货架的层数越低,目标函数值越小,由此得出管理者在布置存储货位时,应当尽可能地降低货架总层数。
In view of the development of the social economy and constantly growing resident consump⁃tion level,warehouse-style supermarkets which integrate the functions of warehousing with sales,and whole⁃sale with retail have gained great popularity.This type of supermarkets relies on warehouse-style commodity display to reduce intermediate storage and secondary transportation costs.Though master package and high turnover of the commodities can cover procurement costs and quality losses,they may also require more ardu⁃ous handling.However,due to space constraints,large handling devices are not viable options inside supermar⁃kets.Therefore,it is very necessary to optimize the allocation of cargo space in warehouse-type supermarkets to reduce the handling workload.On the other hand,previous researches on cargo space optimization only examined shelves with only one I/O,that is,the goods were transported from different starting points to a common destination.But in reality,a warehouse-type supermarket needs to move goods from storage shelves to the corresponding sales shelves,that is,from different starting points to different destinations.Therefore,in this paper,in order to reduce the handling workload in warehouse-type supermarkets,taking into account constraints such as shelf center of gravity and aggregation of same-category goods,we established a mathematical model to solve the correspond⁃ing storage space assignment problem,and assigned goods to suitable slots according to certain assignment rules,while ensuring that goods of the same kind are placed as concentrated as possible,the center of gravity of the shelf does not exceed a certain height,and the time required to move goods to their corresponding sales slots is minimized.Then,to solve the model,we designed an improved adaptive crossover mutation genetic algo⁃rithm which employed three different neighborhood search operators to improve the mutation operator.The result of a numerical analysis showed that the improved adaptive crossover mutation genetic a
作者
徐泽宇
杨双
XU Zeyu;YANG Shuang(School of Management,Jinan University,Guangzhou 510000,China)
出处
《物流技术》
2024年第1期62-74,共13页
Logistics Technology
关键词
货位优化
储销混合货位
仓储式超市
改进遗传算法
cargo space optimization
warehousing-sales mixed cargo space
warehouse-type supermar⁃ket
improved genetic algorithm
