摘要
针对拣选型立体仓库的货架安全、出入库效率和拣选工人的有效工作时长的问题,建立以出入库作业时间、货架整体稳定性和货物从高处或低处拣选时消耗的能量为目标函数,构建多目标货位优化模型。然后对多目标优化模型进行加权归一化处理,对于处理后的目标函数运用遗传算法求解,并结合算例,验证遗传算法解决拣选型立体仓库货位优化问题的有效性。
In order to solve the problems of shelf safety, warehousing efficiency and effective working hours of picking workers in the picking warehouse, a multi-objective location optimization model is established with the warehousing operation time, overall shelf stability and energy consumption when goods are picked from high or low places as objective functions. Then the multi-objective optimization model is weighted and normalized. The genetic algorithm is solved for the processed objective function, and the effectiveness of the genetic algorithm to solve the problem of sorting stereo warehouse location optimization is verified.
作者
高楠
王莲花
李筱烨
GAO Nan;WANG Lianhua;LI Xiaoye(School of Information, Beijing Wuzi University, Beijing 101149, China)
出处
《物流科技》
2019年第5期153-157,共5页
Logistics Sci-Tech
基金
北京市智能物流系统协同创新中心资助项目(PXM2017_014214_000013)
关键词
拣选型立体仓库
货位分配
遗传算法
多目标规划
picking stereo warehouse
location allocation
genetic algorithm
multi-objective planing
