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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.
Drosophila optimization algorithm is a kind of intelligent algorithm to solve fruit foraging problem to solve optimization problem. However, in order to avoid the defect that it is easy to fall into local extreme during optimization, a new fruit fly optimization algorithm based on chaotic disturbance is proposed. In the process of iteration, the optimal individuals are obtained by the basic Drosophila algorithm firstly, and then the chaotic perturbation strategy is introduced to the optimal individuals to enhance the possibility of obtaining the global optimal solution. At the same time, the chaos disturbance And improve the ability of the algorithm to jump out of the local optimum and find the global optimum.The simulation results of six classical test functions show that the convergence speed, convergence accuracy and robustness of the new algorithm are more obvious than the basic Drosophila optimization algorithm Advantage.