Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0360-8352(02)00030-X
Title: Variable period adaptive genetic algorithm
Authors: Chew, E.P. 
Ong, C.J. 
Lim, K.H.
Keywords: Genetic algorithm
Self-adapting
Variable period
Issue Date: 11-Apr-2002
Source: Chew, E.P., Ong, C.J., Lim, K.H. (2002-04-11). Variable period adaptive genetic algorithm. Computers and Industrial Engineering 42 (2-4) : 353-360. ScholarBank@NUS Repository. https://doi.org/10.1016/S0360-8352(02)00030-X
Abstract: Self-adapting genetic algorithm has two main factors contributing to its improved performance. The first is the effect of the progress of the evolution process where the fitness of the population improves as the number of generation increases. The second is the improvement due to the choice of the probabilities for the various genetic operators. In this paper, we propose a scheme that isolates the contributions of these two factors through the introduction of two competing populations. These two concurrent populations provide the necessary feedback to either prolong the duration of a good choice of the parameter setting or shorten that of a poor choice. Results from several numerical experiments have shown that the proposed scheme provides favorable performance over existing methods. © 2002 Elsevier Science Ltd. All rights reserved.
Source Title: Computers and Industrial Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/72425
ISSN: 03608352
DOI: 10.1016/S0360-8352(02)00030-X
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