A new dynamical evolutionary algorithm based on statistical mechanics

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 po...

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Bibliographic Details
Published in:Journal of computer science and technology 2003-05, Vol.18 (3), p.361-368
Main Authors: Li, YuanXiang, Zou, XiuFen, Kang, LiShan, Zbigniew, Michalewicz
Format: Article
Language:English
Subjects:
Algorithms
Computer simulation
Entropy
Evolutionary algorithms
Genetic algorithms
Mathematical models
Minimization
Molecular dynamics
Optimization
Population (statistical)
Principles
Statistical mechanics
Studies
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Summary: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.
ISSN:1000-9000
1860-4749
DOI:10.1007/BF02948906