改进量子交叉免疫克隆算法及其应用  

Improved quantum crossover immune clonal algorithm and its application

作　　者：戴红伟[1,2] 杨玉[2] 仲兆满[2] 李存华[2] 

机构地区：[1]江苏省海洋资源开发研究院,江苏连云港222005 [2]淮海工学院计算机工程学院,江苏连云港222005

出　　处：《山东大学学报（工学版）》2015年第2期17-21,共5页Journal of Shandong University（Engineering Science）

基　　金：江苏省海洋资源开发研究院开放课题基金资助项目(JSIMR201338);江苏省优秀中青年教师境外研修资助项目;江苏省青蓝工程(2012)资助项目

摘　　要：根据不同交叉算子的互补特性,提出了改进量子交叉免疫克隆算法(improved quantum crossover immune cloanl algorithm,IQCICA)。交叉算子由具有深度挖掘和广度挖掘特征的两种算子组成,并通过适当的参数控制两种算子的选择。将该算法应用于著名的组合优化问题—旅行商问题(traveling salesman problems,TSP),并将计算结果与其它算法进行了对比分析。仿真结果表明,混合量子交叉免疫克隆选择算法能有效平衡全局和局部搜索能力,有着较好的收敛速度和稳定性。An improved quantum crossover immune clonal algorithm （IQCICA） was proposed based on two crossovers with complementary characteristics. The hybrid crossover consists of two crossovers with exploitation and exploration characteristics respectively. A user-defined parameter was used to select the crossover. The improved algorithm was used to solve the famous combinatorial optimization problems-Traveling Salesman Problems （TSP）. Comparison was also performed with other algorithms. Simulation results showed that the improved algorithm had better convergence and stability, and could effectively balance the global and local search capabilities.

关 键 词：免疫计算 克隆选择算法 混合交叉算子 旅行商问题 组合优化问题 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]