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Natural Genetic Algorithm and Its Performance Analysis

Li G

Open publisher page 1 citations

Abstract

There are three difficult problems in the application of genetic algorithm, namely the parameter control, the premature convergence and the deception problem. Based on genetic algorithm with varying population size, a self adaptive genetic algorithm called natural genetic algorithm (nGA) is proposed. It introduces the population size threshold and the immigrant concepts, and adopts dynamically changing parameters in this paper. The design and structure of the nGA are discussed, and the performance of nGA is also analyzed.

About this research paper

What this paper is about

There are three difficult problems in the application of genetic algorithm, namely the parameter control, the premature convergence and the deception problem. Based on genetic algorithm with varying population size, a self adaptive genetic algorithm called natural genetic algorithm (nGA) is proposed. It introduces the population size threshold and the immigrant concepts, and adopts dynamically changing parameters in this paper. The design and structure of the nGA are discussed, and the performance of nGA is also analyzed.

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Available abstract

There are three difficult problems in the application of genetic algorithm, namely the parameter control, the premature convergence and the deception problem. Based on genetic algorithm with varying population size, a self adaptive genetic algorithm called natural genetic algorithm (nGA) is proposed. It introduces the population size threshold and the immigrant concepts, and adopts dynamically changing parameters in this paper. The design and structure of the nGA are discussed, and the performance of nGA is also analyzed.

Key concepts: Genetic algorithm, Premature convergence, Quality control and genetic algorithms, Cultural algorithm, Computer science, Algorithm, Convergence (economics), Population-based incremental learning

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