改进量子交叉免疫克隆算法及其应用

doi:10.6040/j.issn.1672-3961.2.2014.211

山东大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (2): 17-21.doi: 10.6040/j.issn.1672-3961.2.2014.211

改进量子交叉免疫克隆算法及其应用

戴红伟^1,2, 杨玉², 仲兆满², 李存华²

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

收稿日期:2014-05-23 修回日期:2014-10-15 出版日期:2015-04-20 发布日期:2014-05-23
作者简介:戴红伟(1975-),男,河南新郑人,副教授,博士,主要研究方向为智能计算,复杂网络等.E-mail:hongweidai@hotmail.com
基金资助:
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

Improved quantum crossover immune clonal algorithm and its application

DAI Hongwei^1,2, YANG Yu², ZHONG Zhaoman², LI Cunhua²

1. Jiangsu Marine Resources Development Research Institute, Lianyungang 222005, Jiangsu, China;
2. School of Computer Engineering, Huaihai Institute of Technology, Lianyungang 222005, Jiangsu, China

Received:2014-05-23 Revised:2014-10-15 Online:2015-04-20 Published:2014-05-23

摘要/Abstract

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。

关键词: 混合交叉算子, 组合优化问题, 克隆选择算法, 免疫计算, 旅行商问题

Abstract: 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.

Key words: immune computation, traveling salesman problems, combinatorial optimization problem, clonal selection algorithm, hybrid crossover

中图分类号:

TP399

戴红伟, 杨玉, 仲兆满, 李存华. 改进量子交叉免疫克隆算法及其应用[J]. 山东大学学报(工学版), 2015, 45(2): 17-21.

DAI Hongwei, YANG Yu, ZHONG Zhaoman, LI Cunhua. Improved quantum crossover immune clonal algorithm and its application[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2015, 45(2): 17-21.

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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

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