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Design of Structure Optimization Based on Adaptive Genetic Algorithm

Zhu Chao-yan

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Abstract

The origin and parameters of the simple genetic algorithm(GA) were presented for optimizing the structural systems with discrete variables.In order to improve the convergence of GA and avoid the premature convergence,considering that the different choices of crossover and mutation will influence GA on search ability and effect,an adaptive GA was introduced.To the effect hereon,the adaptive GA was shown more effective than GA by an example,the computation precision and operating efficiency were all enhanced.

About this research paper

What this paper is about

The origin and parameters of the simple genetic algorithm(GA) were presented for optimizing the structural systems with discrete variables.In order to improve the convergence of GA and avoid the premature convergence,considering that the different choices of crossover and mutation will influence GA on search ability and effect,an adaptive GA was introduced.To the effect hereon,the adaptive GA was shown more effective than GA by an example,the computation precision and operating efficiency were all enhanced.

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Available abstract

The origin and parameters of the simple genetic algorithm(GA) were presented for optimizing the structural systems with discrete variables.In order to improve the convergence of GA and avoid the premature convergence,considering that the different choices of crossover and mutation will influence GA on search ability and effect,an adaptive GA was introduced.To the effect hereon,the adaptive GA was shown more effective than GA by an example,the computation precision and operating efficiency were all enhanced.

Key concepts: Crossover, Genetic algorithm, Convergence (economics), Computation, Premature convergence, Mathematical optimization, Algorithm, Computer science

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