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    Abstract:

    Having no distinctly guided tendency is one of the main weaknesses of Evolutionary Algorithms. In reference to the individuals' life periodicity, an ecological evolution model guided by life period is proposed in this paper. In the model, the guiding sectors are set up at each phase of the life period, and the individuals' evolution is guided by their ecological features within the whole life period. The experimental results show the model's effectiveness.

    Reference
    1  Chen Guo-liang, Wang Xu-fa, Zhuang Zhen-quan et al. Genetic Algorithm and Its Applications. Beijing: People's Post and Tele-Communications Press, 1996 (陈国良,王煦法,庄镇泉等.遗传算法及应用.北京:人民邮电出版社,1996) 2  Srinivas M. Adaptive probabilities of crossover and mutation in genetic algorithms. IEEE Transactions on Systems, Man and Cybernetics, 1994,24(4):656~667 3  Jones T. Crossover, macromutation and population-based search. In: Eshelman L ed. Proceedings of the 6th International Conference on Genetic Algorithms. San Francisco, CA: Morgan Kaufmann Publishers, 1995. 73~80 4  Cavaretta M J. Using a culture algorithm to control genetic operators. In: Fogel D D ed. Proceedings of the 3rd Annual Conference on Evolutionary Programming. Cambridge, MA: MIT Press, 1994. 158~166 5  Sebag M, Ravise C, Schoenauer M. Controlling evolution by means of machine learning. Evolutionary Programming V, 1996. 57~66 6  Huberman B A. The Ecology of Computation. The Netherlands: Elservier Science Publishers B.V., 1988 7  Rumelhart D B, Mcdelland J. Exploration in Parallel Distributed Processing. Cambridge, MA: MIT Press, 1988 8  Heragu S S. Facility layout. EJORDT, 1992,57(2):135~304 9  Heragu S S. Experimental analysis of simulated annealing based algorithms for the layout problem. EJORDT, 1992,57(2):190~202 10  Nissen V. Solving the quadratic assignment problem with clues from nature. IEEE Transactions on Neural Networks, 1994,5(1):66~72
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曹先彬,许凯,章洁,王煦法.基于生命期引导的生态进化模型.软件学报,2000,11(6):823-828

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History
  • Received:March 09,1999
  • Revised:June 11,1999
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