【摘要】 为了解决传统基因表达式编程(GEP)无法发现多模函数的所有最优解的问题,将小生境概念引入到基因表达式编程中。分析了传统GEP算法在多模函数优化方面的不足,提出了小生境半径的自适应调整策略AMNR,提出了基于小生境基因表达式编程的多模函数优化算法NGEP-MFO,扩展了传统GEP的应用领域。实验表明,相对于传统GEP,NGEP-MFO能大幅提高发现所有最优解的成功率和判定最优解的准确度。更多还原

【Abstract】 Traditional Gene Expression Programming(GEP) can not discover all optimum solutions for specific multimodal function.To solve this problem,the niche technology was applied to GEP.The limitation of the existing optimization for multimodal function based on GEP was analyzed.A modification strategy with niche radius named AMNR(Adaptive Modification with Niche Radius) and an algorithm named NGEP-MFO(Multimodal Function Optimization based on Niche GEP) were proposed.The application domain of traditional GEP was extended.Experiments showed that compared with traditional GEP,NGEP-MFO can improve the successful ratio and accuracy greatly for identifying all optimum solutions.更多还原