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https://hdl.handle.net/2440/46756
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Type: | Journal article |
Title: | A genetic algorithm calibration method based on convergence due to genetic drift |
Author: | Gibbs, M. Dandy, G. Maier, H. |
Citation: | Information Sciences, 2008; 178(14):2857-2869 |
Publisher: | Elsevier Science Inc |
Issue Date: | 2008 |
ISSN: | 0020-0255 1872-6291 |
Statement of Responsibility: | Matthew S. Gibbs, Graeme C. Dandy and Holger R. Maier |
Abstract: | The selection of Genetic Algorithm (GA) parameters is a difficult problem, and if not addressed adequately, solutions of good quality are unlikely to be found. A number of approaches have been developed to assist in the calibration of GAs, however there does not exist an accepted method to determine the parameter values. In this paper, a GA calibration methodology is proposed based on the convergence of the population due to genetic drift, to allow suitable GA parameter values to be determined without requiring a trial-and-error approach. The proposed GA calibration method is compared to another GA calibration method, as well as typical parameter values, and is found to regularly lead the GA to better solutions, on a wide range of test functions. The simplicity and general applicability of the proposed approach allows suitable GA parameter values to be estimated for a wide range of situations. © 2008 Elsevier Inc. All rights reserved. |
Description: | Copyright © 2008 Elsevier Inc. All rights reserved. |
DOI: | 10.1016/j.ins.2008.03.012 |
Description (link): | http://www.elsevier.com/wps/find/journaldescription.cws_home/505730/description |
Published version: | http://dx.doi.org/10.1016/j.ins.2008.03.012 |
Appears in Collections: | Aurora harvest 6 Civil and Environmental Engineering publications Environment Institute publications |
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