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2013•Applied Mechanics and MaterialsRequires access

Application of Hybrid Genetic Algorithm in Control Network Adjustment

Wei Chen

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Abstract

In this paper a hybrid genetic algorithm which consists of the simplex method and the genetic algorithm is proposed for the defect of poor local search ability of genetic algorithm. The hybrid genetic algorithm has the advantages of good global convergence of the genetic algorithm and excellent local search ablility of the simplex method and can improve search speed and calculation accuracy.The hybrid algorithm is applied to the control network adjustment and experimental results demonstrates the effectiveness and superiority of the algorithm.

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What this paper is about

In this paper a hybrid genetic algorithm which consists of the simplex method and the genetic algorithm is proposed for the defect of poor local search ability of genetic algorithm. The hybrid genetic algorithm has the advantages of good global convergence of the genetic algorithm and excellent local search ablility of the simplex method and can improve search speed and calculation accuracy.The hybrid algorithm is applied to the control network adjustment and experimental results demonstrates the effectiveness and superiority of the algorithm.

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Available abstract

In this paper a hybrid genetic algorithm which consists of the simplex method and the genetic algorithm is proposed for the defect of poor local search ability of genetic algorithm. The hybrid genetic algorithm has the advantages of good global convergence of the genetic algorithm and excellent local search ablility of the simplex method and can improve search speed and calculation accuracy.The hybrid algorithm is applied to the control network adjustment and experimental results demonstrates the effectiveness and superiority of the algorithm.

Key concepts: Population-based incremental learning, Genetic algorithm, Simplex algorithm, Convergence (economics), Algorithm, Simplex, Computer science, Meta-optimization

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