基于小生境的GEP新算法

New GEP algorithm based on niche

为了克服传统基因表达式编程在演化后期容易丢失群体多样性的缺陷,避免出现早熟收敛,提出基于小生境的基因表达式编程新算法。将相同适应值的个体组成一个小生境,如果相同适应值的个体数量超过小生境容量x,则将超出的个体放入演化池中进行重新初始化。实验结果表明,使用这种基于小生境的基因表达式编程新算法能在整个演化过程中保持丰富的群体多样性,并能够更有效地避免算法的早熟收敛,更准确地求出问题的最优解。

New gene expression programming based on niche is proposed to overcome the shortcoming of basic gene expression programming that it is easy to lose the population diverse in the later period of evolution, and then to avoid premature conver- gence. The algorithm uses a niche to contain the individuals of same fitness. When a niche is filled to capacity, other individuals who want to join the niche will be initialized. Experiments show that the new GEP algorithm based on niche can preserve popula- tion diversity and then can avoid premature convergence effectively, greatly improve the ability to search the optimal resolution.