Adaptive Simulated Annealing Genetic Algorithm for System Identification Engineering

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Genetic algorithms and simulated annealing are leading methods of search and optimization. This paper proposes an efficient hybrid genetic 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.
Publisher
Elsevier
Issue Date
2005
Keywords

Genetic algorithm; Simulated annealing; System identification

Citation

Advances in Engineering Software, Volume 37, Issue 6, June 2006, Pages 406-418

ISSN
0952-1976
DOI
10.1016/j.advengsoft.2005.08.002
URI
http://hdl.handle.net/10203/8288
Appears in Collection
EE-Journal Papers(저널논문)

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