An Improved Firefly Algorithm and its Application in Washout Optimization

doi:10.16182/j.issn1004731x.joss.19-0226

Abstract

Abstract: To improve the accuracy of the firefly algorithm (FA) and solve the problem of fixed iteration step of the algorithm and easy to fall into local optimum, an improved firefly algorithm is proposed, i.e., EOFA. The EOFA algorithm combines the strong local search ability of extremal optimization algorithm with the strong search ability of firefly algorithm, and adopts the iterative step size of inverted s-type function to improve the optimization ability of the firefly algorithm. The simulation results of function optimization test shows that the improved EOFA algorithm has better optimization performance than firefly algorithm and particle swarm optimization (PSO) algorithm. The improved algorithm is applied to parameter optimization of washout algorithm, and satisfactory result is obtained.

Key words: firefly algorithm, extremum optimization, wash out algorithm, perception error, parameter optimization

CLC Number:

TP391.9

Wang Hui, Lü Xingshun. An Improved Firefly Algorithm and its Application in Washout Optimization[J]. Journal of System Simulation, 2021, 33(2): 306-314.

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