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2005•Journal of Guangzhou UniversityRequires access

A mixed genetic simulated annealing algorithm and its application

Miao Liu

Open publisher page 2 citations

Abstract

This paper analyzes the advantages and disadvantages of genetic algorithm and simulated annealing, brings forward a mixed genetic and simulated annealing algorithm, and optimizes its implementation. This paper also gives the result and example of using the mixed genetic simulated annealing algorithm to solve TSP problem. From the analysis and experiment result, it is concluded that this algorithm is superior to Genetic Algorithm and Simulated Annealing.

About this research paper

What this paper is about

This paper analyzes the advantages and disadvantages of genetic algorithm and simulated annealing, brings forward a mixed genetic and simulated annealing algorithm, and optimizes its implementation. This paper also gives the result and example of using the mixed genetic simulated annealing algorithm to solve TSP problem. From the analysis and experiment result, it is concluded that this algorithm is superior to Genetic Algorithm and Simulated Annealing.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Available abstract

This paper analyzes the advantages and disadvantages of genetic algorithm and simulated annealing, brings forward a mixed genetic and simulated annealing algorithm, and optimizes its implementation. This paper also gives the result and example of using the mixed genetic simulated annealing algorithm to solve TSP problem. From the analysis and experiment result, it is concluded that this algorithm is superior to Genetic Algorithm and Simulated Annealing.

Key concepts: Simulated annealing, Adaptive simulated annealing, Genetic algorithm, Algorithm, Annealing (glass), Computer science, Mathematical optimization, Materials science

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