JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2015, Vol. 45 ›› Issue (2): 17-21.doi: 10.6040/j.issn.1672-3961.2.2014.211

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Improved quantum crossover immune clonal algorithm and its application

DAI Hongwei1,2, YANG Yu2, ZHONG Zhaoman2, LI Cunhua2   

  1. 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

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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

CLC Number: 

  • TP399
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