Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
485931 | Procedia Computer Science | 2015 | 10 Pages |
This paper is focused on genetic algorithm with chaotic crossover operator. We have performed some experiments to study possible use of chaos in simulated evolution. A novel genetic algorithm with chaotic optimization operation is proposed to optimization of multimodal functions. As the basis of a new crossing operator a simple equation involving chaos is used, concrete the logistic function. The logistic function is a simple one-parameter function of the second order that shows a chaotic behavior for some values of the parameter. Generally, solution of the logistic function has three areas of its behavior: convergent, periodic and chaotic. We have supposed that the convergent behavior leads to exploitation and the chaotic behavior aids to exploration. The periodic behavior is probably neutral and thus it is a negligible one. Results of our experiments confirm these expectations. A proposed genetic algorithm with chaotic crossover operator leads to more efficient computation in comparison with the traditional genetic algorithm.