免疫遗传算法在TSP求解中的应用

APPLICATION OF IMMUNE GENETIC ALGORITHM TO TSP

基本遗传算法保持群体多样性的能力较差,所以经常在问题求解的过程中得到局部最优解。根据生物的免疫原理提出的一种改进算法———免疫遗传算法。免疫遗传算法主要体现了生物免疫系统中的基因重组、免疫记忆、隔离小生境和免疫元动态等特性,这些特性改进基本遗传算法的群体多样性保持能力。最后结合旅行商问题(TSP)的优化介绍了具体实现方法,实验结果表明该免疫遗传算法有较好的性能。

The ability of keeping the diversity of population is poor in simple genetic algorithm（ SGA）, so SGA often gets the local optimization while solving the optimization programs. An improved algorithm named as Immune Genetic Algorithm（IGA） based on immune principle is presented. IGA embodies the characters of biological immune system （ BIS）, such as gene reproduction,immune memory, niche and meta dynamic function. These characters enhance the ability of keeping the diversity of population in GA. Its application to traveling salesman problem （TSP） shows that IGA performs well on the aspects of search ability and search speed.