Adaptive simulated annealing genetic algorithm for system identification

Genetic algorithms and simulated annealing are leading methods of search and optimization. This paper proposes an efficient hybrid algorithm named ASAGA (Adaptive Simulated Annealing Genetic Algorithm). Genetic algorithms are global search techniques for optimization. However, they are poor at hill-...

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Bibliographic Details
Published in:Engineering applications of artificial intelligence 1996-10, Vol.9 (5), p.523-532
Main Authors: Jeong, Il-kwon, Lee, Ju-jang
Format: Article
Language:English
Subjects:
Genetic algorithm
simulated annealing
system identification
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Summary:Genetic algorithms and simulated annealing are leading methods of search and optimization. This paper proposes an efficient hybrid algorithm named ASAGA (Adaptive Simulated Annealing Genetic Algorithm). Genetic algorithms are global search techniques for optimization. However, they are poor at hill-climbing. Simulated annealing has the ability of probabilistic hill-climbing. Therefore, the two techniques are combined here to produce an adaptive algorithm that has the merits of both genetic algorithms and simulated annealing, by introducing a mutation operator like simulated annealing and an adaptive cooling schedule. The validity and the efficiency of the proposed algorithm are shown by an example involving system identification.
ISSN:0952-1976
1873-6769
DOI:10.1016/0952-1976(96)00049-8