期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：8
页码：17613
DOI：10.15680/IJIRSET.2017.0608302
出版社：S&S Publications
摘要：In this paper, a nature-inspired population based optimization algorithm proposed by Mirjalili in 2015,popularly known as Moth Flame Optimization (MFO), is demonstrated. The main inspiration of this paradigm isnavigation manner of moths in cosmos known as transverse orientation. This orientation is used to solve the variousoptimization problems by mathematical modeling the behavior of the moths to execute optimization. To demonstratethe performance, the MFA (Moth-Flame Algorithm) is applied on six benchmark functions and are compared with theFlower Pollination Algorithm (FPA), Genetic Algorithm (GA), Firefly Algorithm (FA), Particle Swarm optimization(PSO). The statistical output derived using benchmark functions delineates the algorithm’s efficiency is competitiveand promising with another algorithm.
