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2007•Journal of Liaoning Technical UniversityRequires access

Chaotic genetic algorithm for structural optimization with discrete variables

Yingshi Han

Open publisher page 9 citations

Abstract

By use of the properties of periodicity,stochastic property and regularity of chaos,a chaotic approach method is presented for structural optimumal design with discrete variables.Through defining a chaotic operator in the genetic algorithm,a hybrid genetic algorithm for structural optimization with discrete variables,combined the advances of both genetic algorithm and the chaotic design method is presented in this paper,which adopted adaptive annealing penalty factors and penalty function.The numerical results show that the hybrid genetic algorithm has a rather high convergence speed and can locate the global optimization with a rather large probability for solving structural optimal design with discrete variables.

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What this paper is about

By use of the properties of periodicity,stochastic property and regularity of chaos,a chaotic approach method is presented for structural optimumal design with discrete variables.Through defining a chaotic operator in the genetic algorithm,a hybrid genetic algorithm for structural optimization with discrete variables,combined the advances of both genetic algorithm and the chaotic design method is presented in this paper,which adopted adaptive annealing penalty factors and penalty function.The numerical results show that the hybrid genetic algorithm has a rather high convergence speed and can locate the global optimization with a rather large probability for solving structural optimal design with discrete variables.

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Available abstract

By use of the properties of periodicity,stochastic property and regularity of chaos,a chaotic approach method is presented for structural optimumal design with discrete variables.Through defining a chaotic operator in the genetic algorithm,a hybrid genetic algorithm for structural optimization with discrete variables,combined the advances of both genetic algorithm and the chaotic design method is presented in this paper,which adopted adaptive annealing penalty factors and penalty function.The numerical results show that the hybrid genetic algorithm has a rather high convergence speed and can locate the global optimization with a rather large probability for solving structural optimal design with discrete variables.

Key concepts: Chaotic, Mathematical optimization, Simulated annealing, Genetic algorithm, Penalty method, Convergence (economics), Algorithm, Meta-optimization

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