Abstract
The utilization of a storage space can be considerably improved by using dense mobile racks. However, it is necessary to perform an optimisation study on the order picking to reduce the time cost as much as possible. According to the channel location information that needs to be sorted, the multiple orders are divided into different batches by using hierarchical clustering. On this basis, a mathematical model for the virtual order clusters formed in the batches is established to optimize the order cluster picking and rack position movement, with the minimum picking time as the objective. For this model, a hybrid genetic algorithm is designed, and the characteristics of the different examples and solution algorithms are further analysed to provide a reference for the solution of the order picking optimisation problem in a dense mobile rack warehouse.
Funder
the National Nature Science Foundation of China
the Beijing Social Science Foundation key project
Beijing the Great Wall scholars’ program
Beijing Tongzhou canal plan “leading talent plan”
Beijing Intelligent Logistics System Collaborative Innovation Center open topic
funded by the Graduate Science and Technology Innovation Project of Capital University of Economics and Business
Publisher
Public Library of Science (PLoS)
Reference21 articles.
1. Li L. Automatic dense warehouse apparatus. U.S. Patent Application 15/499,107; 2017.
2. Kaukl CV, Cai X, Bhat AS, Eng M. High density automated storage and retrieval system. U.S. Patent Application 15/787,597; 2017.
3. Optimal zone boundaries for two-class-based compact three-dimensional automated storage and retrieval systems;Y Yu;IIE Transactions,2009
4. Response time analysis of a live-cube compact storage system with two storage classes;N Zaerpour;IISE Transactions,2017
5. Optimal two-class-based storage in a live-cube compact storage system;N Zaerpour;IISE Transactions,2016
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献