Journal
CHAOS
Volume 29, Issue 1, Pages -Publisher
AIP Publishing
DOI: 10.1063/1.5048299
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Funding
- DICYT (Scientific and Technological Research Bureau)
- Department of Industrial Engineering of the University of Santiago of Chile (USACH)
- FONDECYT (Chile) [11160542]
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This work proposes a new edge about the Chaotic Genetic Algorithm (CGA) and the importance of the entropy in the initial population. Inspired by chaos theory, the CGA uses chaotic maps to modify the stochastic parameters of Genetic Algorithm. The algorithm modifies the parameters of the initial population using chaotic series and then analyzes the entropy of such population. This strategy exhibits the relationship between entropy and performance optimization in complex search spaces. Our study includes the optimization of nine benchmark functions using eight different chaotic maps for each of the benchmark functions. The numerical experiment demonstrates a direct relation between entropy and performance of the algorithm. Published under license by AIP Publishing.
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