A Modified Firefly Algorithm with mating behavior
Firefly algorithm (FA), as one promising optimization algorithms, has been popularly used for various programing problems.To address the shortcomings of FA, i.e., local optimum and slow convergence, this study tends to modify the typical FA by introducing a mating behavior, to improve the global searching capability.In particular, all fireflies are split into sub-populations, and each group evolved independently by following the typical process of FA and the best ones are selected to conduct mating behaviors, which might enhance the generation diversity.With other popular optimization algorithms of genetic algorithm (GA), particle swarm optimization (PSO) and typical FA as the benchmark models, the experimental study confirms the effectiveness of the novel model in terms of time-savings and better solutions.
Firefly algorithm Optimization Artificial intelligence
Lean Yu Zishu Wang Ling Tang
School of Economics and Management, Beijing University of Chemical Technology, Beijing, 100029, China
国内会议
长春
英文
563-568
2015-07-25（万方平台首次上网日期，不代表论文的发表时间）