Journal of Computer Science and Technology

, Volume 18, Issue 3, pp 361–368

A new dynamical evolutionary algorithm based on statistical mechanics

  • YuanXiang Li
  • XiuFen Zou
  • LiShan Kang
  • Michalewicz Zbigniew
Correspondence

DOI: 10.1007/BF02948906

Cite this article as:
Li, Y., Zou, X., Kang, L. et al. J. Comput. Sci. & Technol. (2003) 18: 361. doi:10.1007/BF02948906

Abstract

In this paper, a new dynamical evolutionary algorithm (DEA) is presented based on the theory of statistical mechanics. The novelty of this kind of dynamical evolutionary algorithm is that all individuals in a population (called particles in a dynamical system) are running and searching with their population evolving driven by a new selecting mechanism. This mechanism simulates the principle of molecular dynamics, which is easy to design and implement. A basic theoretical analysis for the dynamical evolutionary algorithm is given and as a consequence two stopping criteria of the algorithm are derived from the principle of energy minimization and the law of entropy increasing. In order to verify the effectiveness of the scheme, DEA is applied to solving some typical numerical function minimization problems which are poorly solved by traditional evolutionary algorithms. The experimental results show that DEA is fast and reliable.

Keywords

dynamical evolutionary algorithm statistical mechanics stopping criterion dynamical system 

Copyright information

© Science Press, Beijing China and Allerton Press Inc. 2003

Authors and Affiliations

  • YuanXiang Li
    • 1
  • XiuFen Zou
    • 1
  • LiShan Kang
    • 1
  • Michalewicz Zbigniew
    • 2
  1. 1.Software Engineering LaboratoryWuhan UniversityWuhanP.R. China
  2. 2.Computer Science DepartmentUniversity of North Carolina at CharlotteCharlotteUSA

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