Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering

A Novel Ant Colony Algorithm with Mutation Operations of Genetic Algorithm for TSP

Authors
Bencan Gong, Peng Chen
Corresponding Author
Bencan Gong
Available Online April 2015.
DOI
https://doi.org/10.2991/isrme-15.2015.159How to use a DOI?
Keywords
Ant colony algorithm; Mutation operations; Genetic algorithm; TSP
Abstract

Ant colony algorithm (ACA) is a very effective way for traveling salesman problem (TSP) due to the positive feedback and the distributed parallel computing mechanism. But it has many drawbacks, for example, long search time, precocity and stagnation. In order to speed up convergence rate and ensure the global search ability, a novel ant colony algorithm was proposed. After every round of search, it uses mutation operations of genetic algorithm to optimize tours and quicken the convergence by comparing path length before and after variation. Experiments show that the improved ant colony algorithm can overcome prematurity and obtain the higher solution accuracy than ACA.

Copyright
© 2015, 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 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
Series
Advances in Intelligent Systems Research
Publication Date
April 2015
ISBN
978-94-62520-59-2
ISSN
1951-6851
DOI
https://doi.org/10.2991/isrme-15.2015.159How to use a DOI?
Copyright
© 2015, 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  - Bencan Gong
AU  - Peng Chen
PY  - 2015/04
DA  - 2015/04
TI  - A Novel Ant Colony Algorithm with Mutation Operations of Genetic Algorithm for TSP
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 784
EP  - 787
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.159
DO  - https://doi.org/10.2991/isrme-15.2015.159
ID  - Gong2015/04
ER  -