李宗岳, 陈志军, 李名远. 基于混沌扰动策略的果蝇优化算法[J]. 微电子学与计算机, 2016, 33(7): 64-68.
引用本文: 李宗岳, 陈志军, 李名远. 基于混沌扰动策略的果蝇优化算法[J]. 微电子学与计算机, 2016, 33(7): 64-68.
LI Zong-yue, CHEN Zhi-jun, LI Ming-yuan. Fruit Fly Optimization Algorithm Based on Chaotic Inerrupt[J]. Microelectronics & Computer, 2016, 33(7): 64-68.
Citation: LI Zong-yue, CHEN Zhi-jun, LI Ming-yuan. Fruit Fly Optimization Algorithm Based on Chaotic Inerrupt[J]. Microelectronics & Computer, 2016, 33(7): 64-68.

基于混沌扰动策略的果蝇优化算法

Fruit Fly Optimization Algorithm Based on Chaotic Inerrupt

  • 摘要: 果蝇优化算法是模拟果蝇觅食的一种解决优化问题的智能算法, 但是为了避免其在优化过程中容易陷入局部极值的缺陷, 提出一种新的基于混沌扰动的果蝇优化算法.在迭代过程中, 首先利用基本果蝇算法获得最优个体, 然后对最优个体引入混沌扰动策略, 增强获得全局最优解的可能性.同时通过动态变化系数η调整在迭代寻求过程中混沌扰动变量的值, 提高算法跳出局部最优和寻找全局最优的能力.对6个经典测试函数的仿真结果表明, 新算法的收敛速度、收敛精度和鲁棒性方面比基本果蝇优化算法具有明显优势.

     

    Abstract: This paper puts forward a new algorithm based on chaotic inerrupt. Firstly the current optimal individual is gained by standard fruit fly optimization algorithm, then chaotic interrupt is added to the current optimal individual to increase the probability of getting the ultimate global optimum. Meanwhile, the value of chaotic variables in the iterative process is adjusted by dynamic variation coefficientηto enhance the ability to escape from the local optimum and seek the global optimum. Simulation results of six classical test functions show that the novel improved algorithm has obvious advantages on convergence precision, convergence speed and robustness.

     

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