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New fuzzy adaptive simulated annealing genetic algorithm

Wei Wei

Open publisher page 13 citations

Abstract

Due to shortcomings of genetic algorithm that its convergence speed is slow and it is often premature convergence,an improved genetic algorithm,fuzzy adaptive simulated annealing genetic algorithm(FASAGA),is presented by integrating fuzzy inference,simulated annealing algorithm and adaptive mechanism.Then the performance and the characteristic of this method are analyzed.Simulation results illustrate that FASAGA has better convergence speed and optimal results than standard genetic algorithm.

About this research paper

What this paper is about

Due to shortcomings of genetic algorithm that its convergence speed is slow and it is often premature convergence,an improved genetic algorithm,fuzzy adaptive simulated annealing genetic algorithm(FASAGA),is presented by integrating fuzzy inference,simulated annealing algorithm and adaptive mechanism.Then the performance and the characteristic of this method are analyzed.Simulation results illustrate that FASAGA has better convergence speed and optimal results than standard genetic algorithm.

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OpenAlex reports 13 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Due to shortcomings of genetic algorithm that its convergence speed is slow and it is often premature convergence,an improved genetic algorithm,fuzzy adaptive simulated annealing genetic algorithm(FASAGA),is presented by integrating fuzzy inference,simulated annealing algorithm and adaptive mechanism.Then the performance and the characteristic of this method are analyzed.Simulation results illustrate that FASAGA has better convergence speed and optimal results than standard genetic algorithm.

Key concepts: Simulated annealing, Adaptive simulated annealing, Genetic algorithm, Premature convergence, Convergence (economics), Fuzzy logic, Algorithm, Computer science

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