Journal of Shanghai Jiaotong University ›› 2012, Vol. 46 ›› Issue (02): 239-244.

• Automation Technique, Computer Technology • Previous Articles     Next Articles

Immune Evolutionary Algorithm Reusing Excellent Genes of Antibody

 YANG  Guan-Ci-1, 2 , MA  Xin-1, LI  Shao-Bo-1, 2 , ZHONG  Yong-2, YU  Li-Ya-1   

  1. (1 Key Laboratory of Advanced Manufacturing Technology of Ministry of Education,Guizhou University, Guiyang 550003, China; 2Chengdu Institute of Computer Applications,Chinese Academy of Sciences, Chengdu 610041, China)
  • Received:2010-12-25 Online:2012-02-28 Published:2012-02-28

Abstract: By expounding the ideological origin of improving the clonal selection algorithm through the analysis of the specific phenomenon, the method to extract excellent gene schema to fill a memory pool from antibody set, to package excellent gene segment, and to replace low affinity antibody with high affinity antibody with probability from mutation antibody population during updating memory antibody population was designed based on clonal selection principle and algorithm, and then an improved clonal selection algorithm reusing excellent gene segment was put forward. Refering to the framework of strength Pareto evolutionary algorithm, the immune evolutionary algorithm reusing excellent genes of antibody (RGIEM) was proposed, which implements the genetic operation such as selection, crossover and recombinant by applying the improved clonal selection algorithm. Taking a series of multiobjective 0/1 knapsack problems to check RGIEA’s performance, the results show that RGIEA is capable of maintaining the diversity of population and obtaining solutions approximating to Pareto front.

Key words: clonal selection, strength Pareto evolutionary algorithm (SPEA), gene mining

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