Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)

Application of An Improved Genetic Algorithm with The Search Space Compression in TSP

Authors
YI Song, Nini Wei
Corresponding Author
YI Song
Available Online April 2013.
DOI
10.2991/icsem.2013.103How to use a DOI?
Keywords
TSP , Genetic Algorithm, incomplete evolution, search space compression
Abstract

The Traveling Salesman Problem is a combinatorial optimization problem, the problem has been shown to belong to the NPC problem, the possible solution of Traveling Salesman Problem and the scale of the cities have the exponential relation, so the more bigger of the scale. In this paper, improve the search process of the genetic algorithm by introducing the idea is to compress the search space. The simulation results show that for solving the TSP, the algorithm can quickly obtain multiple high-quality solutions. It can reduce the blindness of random search and accelerate convergence of the algorithm.

Copyright
© 2013, 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 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
Series
Advances in Intelligent Systems Research
Publication Date
April 2013
ISBN
10.2991/icsem.2013.103
ISSN
1951-6851
DOI
10.2991/icsem.2013.103How to use a DOI?
Copyright
© 2013, 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  - YI Song
AU  - Nini Wei
PY  - 2013/04
DA  - 2013/04
TI  - Application of An Improved Genetic Algorithm with The Search Space Compression in TSP
BT  - Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
PB  - Atlantis Press
SP  - 529
EP  - 532
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.103
DO  - 10.2991/icsem.2013.103
ID  - Song2013/04
ER  -