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中文摘要：
针对基本萤火虫算法易于早熟收敛、求解精度不高、后收敛较慢等问题，为提高算法的快速性，提出一种改进萤火虫算法局部搜索能力的优化算法。采用切比雪夫混沌映射函数生成混沌序列，初始化萤火虫群体以获得较优初始解，在算法迭代过程采用设计的混沌局部搜索算子进行局部搜索以增强局部开采寻优能力，同时进行动态变化搜索区域以提高收敛速度。仿真结果表明，改进算法与萤火虫算法相比，在寻优精度和收敛速度方面都有明显提高。
英文摘要：
To overcome the disadvantages of easy premature convergence, low solution precision and slow convergence in the firefly algorithm （FA）, an improved chaotic firefly algorithm （ICFA） to enhance the local search ability is proposed. ICFA generates chaotic sequence by using the Chebyshev chaotic mapping function, and obtains a good initial solution by initializing the firefly population. In the iterative process of the algorithm, ICFA uses the designed chaotic local search operator to search locally better solution in order to enhance the local exploitation ability, meanwhile dynamicly changes the search area to improve the convergence rate. The results of simulation show that ICFA is superior to FA in terms of accuracy and convergence speed.
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