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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2014 - 9

Simplified Genetic Algorithm: Simplify and Improve RGA for Parameter Optimizations

NGAMTAWEE, R. See more information about NGAMTAWEE, R. on SCOPUS See more information about NGAMTAWEE, R. on IEEExplore See more information about NGAMTAWEE, R. on Web of Science, WARDKEIN, P. See more information about WARDKEIN, P. on SCOPUS See more information about WARDKEIN, P. on SCOPUS See more information about WARDKEIN, P. on Web of Science
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Download PDF pdficon (1,476 KB) | Citation | Downloads: 371 | Views: 2,110

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

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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.

References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 32,537 TCR
SCOPUS® Citations for all references: 8,009 TCR

Web of Science® Average Citations per reference: 1,205 ACR
SCOPUS® Average Citations per reference: 297 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-01-21 04:44 in 80 seconds.

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Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

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