Proceedings of the 2016 3rd International Conference on Mechatronics and Information Technology

Improved Fitness Proportionate Selection-Based Genetic Algorithm

Authors
Fengrui Yu, Xueliang Fu, Honghui Li, Gaifang Dong
Corresponding Author
Fengrui Yu
Available Online April 2016.
DOI
https://doi.org/10.2991/icmit-16.2016.26How to use a DOI?
Keywords
genetic algorithm (GA), fitness proportionate selection, roulette wheel selection, travelling salesman problem (TSP)
Abstract
Genetic algorithms are typical swarm intelligence techniques based on the mechanics of natural selection and natural genetics , which combines artificial survival of the fittest concept with genetic operations abstracted from nature. Since the genetic algorithm has good global search capability, as well as the parallel nature of other advantages, it has been widely used in combinatorial optimization, machine learning, signal processing field, adaptive control and artificial life and so on. It is one of the key technologies related to modern intelligent calculation. Fitness proportionate selection, as a common selection method for GA, is usually implemented with method of roulette wheel selection. In this paper,An improved selection method based on fitness proportionate selection was presented. Computational results show that the method which proposed in this paper improved the result precision and better astringency by solving TSP problem.
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Proceedings
2016 3rd International Conference on Mechatronics and Information Technology
Part of series
Advances in Computer Science Research
Publication Date
April 2016
ISBN
978-94-6252-184-1
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmit-16.2016.26How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Fengrui Yu
AU  - Xueliang Fu
AU  - Honghui Li
AU  - Gaifang Dong
PY  - 2016/04
DA  - 2016/04
TI  - Improved Fitness Proportionate Selection-Based Genetic Algorithm
BT  - 2016 3rd International Conference on Mechatronics and Information Technology
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmit-16.2016.26
DO  - https://doi.org/10.2991/icmit-16.2016.26
ID  - Yu2016/04
ER  -