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The Research of Solving TSP Based On Genetic Algorithm

Ke Wang

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Abstract

The paper focuses on the application research of genetic algorithms,it has completed the following two aspects of the work: 1) First,making the necessary genetic algorithm theory expounded,discussing the implementation of genetic algorithm in the application development;presented a description of the algorithm realization of the simple process in C language;2) The main applications and the latest research areas of genetic algorithms are briefly described;described the original method to solve the TSP,discussed the application that genetic algorithm solved TSP in the encoded representation and genetic operation operators and other aspects.

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What this paper is about

The paper focuses on the application research of genetic algorithms,it has completed the following two aspects of the work: 1) First,making the necessary genetic algorithm theory expounded,discussing the implementation of genetic algorithm in the application development;presented a description of the algorithm realization of the simple process in C language;2) The main applications and the latest research areas of genetic algorithms are briefly described;described the original method to solve the TSP,discussed the application that genetic algorithm solved TSP in the encoded representation and genetic operation operators and other aspects.

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Available abstract

The paper focuses on the application research of genetic algorithms,it has completed the following two aspects of the work: 1) First,making the necessary genetic algorithm theory expounded,discussing the implementation of genetic algorithm in the application development;presented a description of the algorithm realization of the simple process in C language;2) The main applications and the latest research areas of genetic algorithms are briefly described;described the original method to solve the TSP,discussed the application that genetic algorithm solved TSP in the encoded representation and genetic operation operators and other aspects.

Key concepts: Computer science, Genetic algorithm, Genetic representation, Algorithm, Realization (probability), Representation (politics), Process (computing), Cultural algorithm

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