Clone mind evolution algorithm

Authors:
Gang Xie;Xinying Xu;Keming Xie;Zehua Chen
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:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
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 such as clone mutation, clone crossover, clone selection are also introduced. Then the clone mind evolution algorithm (CMEA) is developed by using the diversity principle of antigen-antibody. Not only can CMEA converge to globally optimal solution, but also it solve premature convergence problem efficiently. 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.