Fruit fly optimization algorithm with adaptive parameter
Han Jun-yin · Computer Engineering and Applications Journal · 2014
In order to overcome the problems of FOA, such as low convergence precision and unstable convergence resulted from improper random parameter, an improved FOA is proposed, called Fruit Fly Optimization Algorithm with Adaptive Parameter(FOAAP). In each evolutionary generation, the accurate values describing the characteristics of the overall species are input, 3 digital characteristics C(ExtEntHet) of the contemporary cloud model are obtained by backward cloud generator, then using U conditions membership cloud generator, the parameter Value is adaptively adjusted, which is Fruit Fly's searching distance and direction for food. FOAAP is compared with FOA and other algorithms in reference literatures, experimental results show that FOAAP has the advantages of speeder convergence, higher convergence precision and higher convergence reliability.