摘要
货位分配直接影响着仓库的拣选效率,为提高仓库的拣选效率,提出采用多巷道存储策略,构建以订单体积指数和需求相关性为优化指标的货位分配模型,并采用改进的遗传算法对模型进行仿真.最后对比小、中、大三种仓库规模及不同权重取值下的算例对优化情况的影响.结果表明,通过考虑订单体积指数和需求相关性并采用多巷道存储策略对货位分配进行优化,针对不同仓库规模及权重取值,均能有效提高拣选效率.
The location allocation directly affects the picking efficiency of the warehouse.In order to improve the picking efficiency of the warehouse,a multi-aisle storage strategy is proposed to construct a location allocation model with cube-per-order index and demand correlation as optimization factors,and an improved genetic algorithm is used to simulate the model.Finally,the effects of calculation examples under the three warehouse scales of small,medium and large and different weights on the optimization situation is compared.The results show that by considering the cube-per-order index and demand correlation and adopting the multi-aisle storage strategy to oprimize,the location allocation,the selection of different warehouse scales and weights can effectively improve picking efficiency.
作者
何立华
任海朝
HE Lihua;REN Haichao(School of Economics and Management,China University of Petroleum(East China),Qingdao 266580,Shandong China)
出处
《河南科学》
2021年第9期1525-1533,共9页
Henan Science
基金
国家自然科学基金青年科学基金项目(71501188)
教育部人文社会科学研究规划基金项目(20YJA630022)
山东省自然科学基金项目(ZR2015GM009)。
关键词
订单体积指数
需求相关性
多巷道
货位分配
遗传算法
cube-per-order index
demand correlation
multi-aisle
storage location assignment
genetic algorithm
