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Abstract
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Article Information:
A Fast and Efficient Genetic Evolution Algorithm
Yu-Cheng Liu and Yu-Bin Liu
Corresponding Author: Yu-Cheng Liu
Submitted: December 15, 2012
Accepted: January 19, 2013
Published: May 01, 2013 |
Abstract:
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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.
Key words: Accelerating operator, improved genetic algorithm, search speed, traditional genetic algorithm, , ,
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Cite this Reference:
Yu-Cheng Liu and Yu-Bin Liu, . A Fast and Efficient Genetic Evolution Algorithm. Research Journal of Applied Sciences, Engineering and Technology, (17): 4427-4432.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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