基于免疫遗传算法的TSP求解

Immune Genetic Algorithm for Traveling Salesman Problem

用一种免疫遗传算法(IGA)对TSP问题进行求解。该算法在保留基本遗传算法(SGA)随机全局搜索能力的基础上,引进了生物免疫系统中的免疫应答,抗原记忆,接种疫苗,免疫选择等机制。实验结果表明,免疫遗传算法可有效改善基本遗传算法未成熟收敛等缺陷,提高全局搜索的效率及能力,在TSP求解中取得了满意的结果。

An Immune Genetic Algorithm(IGA) is used to solve traveling salesman problem(TSP). Based on the global search ability of simple genetic algorithm (SGA), it also introduces immune responsion, antigen memory, inoculate vaccine and immunity selection of biological immune systems into SGA. It proves IGA can amend the vice that the SGA can't converge maturity and improve efficiency and ability of globe search. It obtains a satisfying result in solving TSP.