A comprehensive analysis on optimization performance of chaotic evolution and its parameter distribution

In this paper, we analyse and discuss the relationship between optimization performance of chaotic evolution (CE) algorithm and distribution characteristic of chaotic parameter. CE is an evolutionary computation algorithm that simulates chaotic motion of a chaotic system in a search space for implementing optimization. However, its optimization performance, internal process mechanism and optimization principle are not well studied. In this paper, we investigate distribution characteristics of chaotic systems, which support chaotic parameter in CE algorithm. Compared with other two parameter generators, i.e., a quadratic-like random generator and an uniform random generator, CE algorithm with chaotic parameter generated by the logistic map (μ = 4) shows better optimization performance significantly. We also make an algorithm comparison with differential evolution and an algorithm ranking by Friedman test and Bonferroni-Dunn test. The related topics on relationship between optimization performance of CE algorithm and chaotic parameter distribution are analysed and discussed. From these analyses and discussions, it indicates that chaotic parameter distribution is a significant factor that influences optimization performance of CE algorithm.