期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：5
出版社：S.S. Mishra
摘要：Nature inspired meta-heuristic algorithms studies the emergent collective intelligence of groups of simple agents. This behaviour can efficiently be used to find the solutions of various global optimization problems. This paper compares performances of two latest of these algorithms namely Bat and Firefly algorithm for unconstrained optimization problems. Global optima are found using various test functions of different characteristics on the basis of convergence speed and precision.
关键词：Firefly Algorithm; Bat Algorithm; Unconstrained Optimization; Benchmark Functions; Nature-Inspired ;Algorithms.
