Warehouse Optimization Model Based on Genetic Algorithm
Joint Authors
Qin, Guofeng
Li, Jia
Jiang, Nan
Li, Qiyan
Wang, Lisheng
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-10
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
This paper takes Bao Steel logistics automated warehouse system as an example.
The premise is to maintain the focus of the shelf below half of the height of the shelf.
As a result, the cost time of getting or putting goods on the shelf is reduced, and the distance of the same kind of goods is also reduced.
Construct a multiobjective optimization model, using genetic algorithm to optimize problem.
At last, we get a local optimal solution.
Before optimization, the average cost time of getting or putting goods is 4.52996 s, and the average distance of the same kinds of goods is 2.35318 m.
After optimization, the average cost time is 4.28859 s, and the average distance is 1.97366 m.
After analysis, we can draw the conclusion that this model can improve the efficiency of cargo storage.
American Psychological Association (APA)
Qin, Guofeng& Li, Jia& Jiang, Nan& Li, Qiyan& Wang, Lisheng. 2013. Warehouse Optimization Model Based on Genetic Algorithm. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1010109
Modern Language Association (MLA)
Qin, Guofeng…[et al.]. Warehouse Optimization Model Based on Genetic Algorithm. Mathematical Problems in Engineering No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-1010109
American Medical Association (AMA)
Qin, Guofeng& Li, Jia& Jiang, Nan& Li, Qiyan& Wang, Lisheng. Warehouse Optimization Model Based on Genetic Algorithm. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1010109
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1010109