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Simplified Genetic Algorithm: Simplify and Improve RGA for Parameter OptimizationsNGAMTAWEE, R.   , WARDKEIN, P. |
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Author keywords
algorithm, evolutionary computation, genetic algorithms, optimization, particle swarm optimization
References keywords
genetic(14), swarm(11), evolutionary(11), computation(11), algorithms(9), optimization(8), convergence(5), premature(4), intelligence(4), algorithm(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2014-11-30
Volume 14, Issue 4, Year 2014, On page(s): 55 - 64
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.04009
Web of Science Accession Number: 000348772500009
SCOPUS ID: 84921692972
Abstract
The structural complexity and complicated generic operators of Genetic Algorithm (GA) contribute to its slow computational speed. Furthermore, GA and other similar algorithms with a small population size are vulnerable to the problem of premature convergence. Premature convergence causes the algorithms to stagnate and stop searching, giving rise to wasteful computation. Even though the problem can be addressed with a larger population size, computational time is inevitably increased. This research paper has thus proposed Simplified Genetic Algorithm (SimpGA). This algorithm utilizes a one-pair-built-all structure in which only two parent chromosomes are required to produce the entire population (offspring). Rather than relying on the conventional operators, simplified operators, i.e. timer mutation, diform crossover and topmost selection, are used in the proposed SimpGA. In addition, tests are carried out with SimpGA on four test functions and four applications. The experimental results show that SimpGA is simpler to implement and performs well, especially in a small population environment. |
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Stefan cel Mare University of Suceava, Romania
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
