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Finding global minima with a new dynamical evolutionary algorithm

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Wuhan University Journal of Natural Sciences

Abstract

A new dynamical evolutionary algorithm (DEA) based on the theory of statistical mechanics is presented. This algorithm is very different from the traditional evolutionary algorithm and the two novel features are the unique of selecting strategy and the determination of individuals that are selected to crossover and mutate. We use DEA to solve a lot of global optimization problems that are nonlinear, multimodal and multidimensional and obtain satisfactory results.

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Authors and Affiliations

  1. State Key Laboratory of Software Engineering, Wuhan University, 430072, Wuhan, Hubei, China

    Zou Xiu-fen, Kang Li-shan, Li Yuan-xiang & Chen Yu-ping

  2. School of Mathematics and Statistics, Wuhan University, 430072, Wuhan Hubei, China

    Zou Xiu-fen

Authors
  1. Zou Xiu-fen
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  2. Kang Li-shan
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  3. Li Yuan-xiang
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  4. Chen Yu-ping
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Additional information

Foundation item: Supported by the National Natural Science Foundation of China (No. 60133010, NO. 60073043 and No. 700/1042)

Biography: Zou Xiu-fen(1996-), female, Ph. D candidate, Associate professor, research direction: evolutionary computing, parallel computing.

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Xiu-fen, Z., Li-shan, K., Yuan-xiang, L. et al. Finding global minima with a new dynamical evolutionary algorithm. Wuhan Univ. J. Nat. Sci. 7, 157–160 (2002). https://doi.org/10.1007/BF02830305

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  • DOI: https://doi.org/10.1007/BF02830305

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