Research on clone mind evolution algorithm

  • Authors:

  • Gang Xie;Hongbo Guo;Keming Xie;Wenjing Zhao

  • Affiliations:

  • College of Information Engineering, Taiyuan University of Technology, Taiyuan, Shanxi, P.R. China;College of Information Engineering, Taiyuan University of Technology, Taiyuan, Shanxi, P.R. China;College of Information Engineering, Taiyuan University of Technology, Taiyuan, Shanxi, P.R. China;College of Information Engineering, Taiyuan University of Technology, Taiyuan, Shanxi, P.R. China

  • Venue:
  • RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
  • Year:
  • 2005

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Abstract

A new algorithm of evolutionary computing, which combines clone selective algorithm involved in artificial immunity system theory and mind evolution algorithm (MEA) proposed in reference [4], is presented in this paper. Based on similartaxis which is the one of MEA operators, some operators borne by the new algorithm including clone mutation, clone crossover, clone selection, is also introduced. Then the clone mind evolution algorithm (CMEA) is developed by using the diversity principle of antigen-antibody. The simulating results of the representative evaluation function show that the problem of degeneration phenomenon existing in GA and MEA can be perfectly solved, and the rapidity of convergence is evidently improved by CMEA studied in the paper. In the example of the solution to the numerical problem, the search range of solution is expanded and the possibility of finding the optimal solution is increased.