一种新的免疫克隆算法在CVRP问题中的应用

A New Immune Clonal Algorithm and Its Applications to CVRP

基于克隆选择学说,通过引入克隆算子提出一种新的免疫克隆算法,并将其用于求解CVRP问题.该算法采用了克隆增殖、高频变异和克隆选择算子的操作,增加了种群中优秀个体获得克隆增殖实现亲和度成熟的机会,提高抗体群分布的多样性,在深度搜索和广度寻优之间取得了平衡.仿真结果表明,该算法具有良好的全局收敛性和较快的收敛速度,能有效解决CVRP问题.

Based on the clonal selection theory, a new immune clonal algorithm（ICA） was put forward with the cloning operator introduced in to solve the CVRP problem. Furthermore, in the algorithm, the operators of clonal proliferation, super mutation and clonal selection were adopted to provide more opportunities for the excellent individuals in the group to get clonal proliferation so as to realize the affinity maturation, improve the diversity of the distribution of group of immune bodies and realize balance between the searching in depths and the optimizing in widths. Simulation results shows that the algorithm has a remarkable reliability of global convergence and convergence rate to solve effectively the CVRP problem.