Adaptive invading genetic algorithm based on chaos search
一种基于混沌搜索的自适应入侵遗传算法

By introducing the concept of invasion of biological systems into Genetic Algorithm (GA), a chaos-search-based Adaptive Invading Genetic Algorithm (AIGA) was proposed in this paper. The invading population, whose size was dynamically determined, was obtained through Chaos Search (CS). The expansion of the invading population was capable of propagating excellent genes among individuals and optimizing the gene structure of the population. And thus, it made the population evolve towards the global optimum. As a result, the algorithm was able to diminish the probability of being convergent to local minima prematurely. The proposed algorithm was applied to function optimization and pattern classification. And the experimental results show that this algorithm has the merits of fast convergence and global optimization.