Comparisons of Firefly Algorithm with Chaotic Maps

Comparisons of Firefly Algorithm with Chaotic Maps

Shoubao Su1, Yu Su2, Mingjuan Xu3 


1 School of Computer Engineering, Jinling Institute of Technology, Nanjing 211169, China;

2 School of Information & Software Engineering, University of Electronic Science &Technology of China, Chengdu 610054, China;

3 School of Information Engineering, West Anhui University, Lu’an 237012, P.R. China

Firefly Algorithm (FA) is one of the new bio-inspired algorithm driven by the simulation of the flashing behavior of fireflies. To deal with the problems of low accuracy and local convergence in standard FA, the chaos theory is introduced into the evolutionary process of FA. Since chaotic mapping has certainty, ergodicity and stochastic property, by initializing the population of fireflies and replacing the constant value of absorption coefficient with four chaotic maps, the proposed FA increases its convergence rate and resulting precision. Comparisons experimentally show that convergence quality and accuracy are improved, which testify that modified FA with chaos is valid and feasible.