An improved hybrid immune algorithm for multimodal optimization

Jia Liyuan, Zhou Cuihong, He J

Abstract

To improve the efficiency of basic artificial immun e algorithm(AIA),this paper presents an improved hy brid immune algorithm(IHIA) for constrained optimization .To ma intain high diversity ,the fitness of each individu al and concentration were taken into account in determinin g reproduction probability. Many benchmark function s were used to demonstrate the validity of IHIA and the ro le of each design of IHIA. Numerical experiments sh ow that IHIA can reduce the complexity of comutation, and then i ncreases the efficiency of IHIA with the maintenanc e of diversity and convergence in optimizing constrained functions .