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|Title:||On the Design of Diploid Genetic Algorithms for Problem Optimization in Dynamic Environments|
|Publisher:||Institute of Electrical and Electronics Engineers (IEEE)|
|Citation:||2006 IEEE Congress on Evolutionary Computation, Proceedings of, pp. 1362-1369|
|Abstract:||Using diploidy and dominance is one method to enhance the performance of genetic algorithms in dynamic environments. For diploidy genetic algorithms, there are two key design factors: the cardinality of genotypic alleles and the uncertainty in the dominance scheme. This paper investigates the effect of these two factors on the performance of diploidy genetic algorithms in dynamic environments. A generalized diploidy and dominance scheme is proposed for diploidy genetic algorithms, where the cardinality of genotypic alleles and/or the uncertainty in the dominance scheme can be easily tuned and studied. The experimental results show the efficiency of increasing genotypic cardinality rather than introducing uncertainty in the dominance scheme.|
|Rights:||Copyright © 2006 IEEE. Reprinted from 2006 IEEE Congress on Evolutionary Computation, pp. 1362-1369. Doi: 10.1109/CEC.2006.1688467. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Leicester’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to firstname.lastname@example.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.|
|Appears in Collections:||Conference Papers & Presentations, Dept. of Computer Science|
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