Research Article | OPEN ACCESS
A Fast and Efficient Genetic Evolution Algorithm
1Yu-Cheng Liu and 2Yu-Bin Liu
1School of Electrical and Information Engineering, Chongqing University of Science and Technology, Chongqing, China
2School of Continuing Education, Panzhihua University, Panzhihua, China
Research Journal of Applied Sciences, Engineering and Technology 2013 17:4427-4432
Received: December 15, 2012 | Accepted: January 19, 2013 | Published: May 01, 2013
Abstract
This study presents an improved genetic algorithm. The algorithm introduced acceleration operator in the traditional genetic algorithm, effectively reducing the computational complexity. The search speed of the algorithm has been greatly improved, so that it can quickly find the global optimal solution. The accelerating collaborative operator lessons from the thoughts of binary search algorithm combining with the variable step length strategy. The accelerating operator has strong local search ability and crossover and mutation operators have strong global search ability, then combining these operators generates a new Genetic algorithm. The tests on the different functions show that the improved algorithm has the advantages of faster convergence and higher stability in the case of a small population than traditional genetic algorithm and can effectively avoid the premature phenomenon.
Keywords:
Accelerating operator, improved genetic algorithm, search speed, traditional genetic algorithm,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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