具有混沌搜索策略的萤火虫优化算法

Firefly Algorithm with Chaotic Search Strategy

萤火虫算法是一种新颖的仿生群智能优化算法,分析了算法的仿生原理和局限,提出一种改进萤火虫局部搜索能力的优化算法。通过逻辑自映射函数产生混沌序列,引入到萤火虫算法中对精英个体进行混沌优化,同时动态收缩搜索空间以加快收敛速度。改进算法有效结合了基本萤火虫算法的局部搜索能力和混沌算法全局优化能力,对典型函数的仿真测试表明,改进算法显著提高了优化性能,在收敛速度和寻优精度方面优于基本萤火虫算法,适合复杂函数优化问题。

Firefly algorithm（FA） is a novel bionic swarm intelligence optimization method.After analyzing the bionic principle and limitation of FA,by enhancing the local searching ability,an improved firefly algorithm for optimization is proposed.A series of chaotic variables based-on the self-logical mapping function are computed and introduced into FA to optimize the elites of artificial fireflies,thus shrinking the search field dynamically.The improved algorithm takes advantage of the chaotic search to improve the capability of precise search while keep the ability of global search of basic firefly algorithm.Simulation results for benchmark functions show that the proposed algorithm has improved the global optimization ability remarkably,and has advantage of convergence property and accuracy compared with the original FA.