Proceedings of the 2016 International Conference on Engineering Management (Iconf-EM 2016)

Freight Information Matching Based on Quantum Evolutionary Algorithm

Authors
Xiangwei Mu, Yan Chen, Haixia Zhao
Corresponding Author
Xiangwei Mu
Available Online January 2017.
DOI
10.2991/iconfem-16.2016.21How to use a DOI?
Keywords
Freight Information Matching;Quantum Evolutionary Algorithm;Genetic Algorithm
Abstract

In order to improve the efficiency of freight vehicle and cargo matching, a mathematical model was established, which describes target and the related constraints, and quantum evolutionary algorithm was proposed to solve this matching problem. In the experiment, improved quantum evolutionary algorithm was compared with the standard genetic algorithm, and the algorithm parameters were optimized. Experiment results show that quantum evolutionary algorithm has better convergence speed, accuracy and stability, which can efficiently get an optimal freight supply and demand matching plan.

Copyright
© 2016, 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 2016 International Conference on Engineering Management (Iconf-EM 2016)
Series
Advances in Economics, Business and Management Research
Publication Date
January 2017
ISBN
10.2991/iconfem-16.2016.21
ISSN
2352-5428
DOI
10.2991/iconfem-16.2016.21How to use a DOI?
Copyright
© 2016, 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  - Xiangwei Mu
AU  - Yan Chen
AU  - Haixia Zhao
PY  - 2017/01
DA  - 2017/01
TI  - Freight Information Matching Based on Quantum Evolutionary Algorithm
BT  - Proceedings of the 2016 International Conference on Engineering Management (Iconf-EM 2016)
PB  - Atlantis Press
SN  - 2352-5428
UR  - https://doi.org/10.2991/iconfem-16.2016.21
DO  - 10.2991/iconfem-16.2016.21
ID  - Mu2017/01
ER  -