Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

Optimization of Automated Warehouse Location Based on Genetic Algorithm

Authors
Wanlei Wang, Jian Gao, Tianyi Gao, Haiting Zhao
Corresponding Author
Wanlei Wang
Available Online June 2017.
DOI
10.2991/caai-17.2017.70How to use a DOI?
Keywords
logistics; location assignment; genetic algorithm; automated warehouse
Abstract

The automated warehouse built in many enterprises still need through manual intervention or random allocation method for distribution of goods allocation. This distribution does not guarantee that the utilization rate of warehouse is high, especially when more types and a large number of goods, need more scientific and reasonable scheme for the storage of goods, and enhance great application value and practical significance for the competitiveness of enterprises. In order to improve the efficiency and utilization of automated warehouse, we take automated warehouse as the object to study the optimization of the storage location of goods based on the genetic algorithm in this paper.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-360-9
ISSN
1951-6851
DOI
10.2991/caai-17.2017.70How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Wanlei Wang
AU  - Jian Gao
AU  - Tianyi Gao
AU  - Haiting Zhao
PY  - 2017/06
DA  - 2017/06
TI  - Optimization of Automated Warehouse Location Based on Genetic Algorithm
BT  - Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 309
EP  - 313
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.70
DO  - 10.2991/caai-17.2017.70
ID  - Wang2017/06
ER  -