Analysis of partnering strategies in symbiotic evolutionary algorithms

Symbiotic evolutionary algorithms, also called cooperative coevolutionary algorithms, are stochastic search algorithms that imitate the biological coevolution process through symbiotic interactions. In the algorithms, the fitness evaluation of an individual requires first selecting symbiotic partners of the individual. Several partner selection strategies are provided. The goal of this study is to analyze how much partnering strategies can influence the performance of the algorithms. With two types of test-bed problems: the NKC model and the binary string covering problem, extensive experiments are carried out to compare the performance of partnering strategies, using the analysis of variance. The experimental results indicate that there does not exist statistically significant difference in their performance.