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针对果蝇优化算法易陷入早熟收敛、收敛速度慢、寻优精度低的缺点,提出一种基于极坐标编码的果蝇优化算法.为提高果蝇优化算法的寻优精度,采用极坐标编码的形式,以增加单个母体寻优空间表示方法的多样性,并使种群中的个体,在围绕个体的整个超球体内随机搜索,使个体的搜索范围更加广泛.在迭代寻优过程中,根据适应度值和概率调整极角,逐渐降低观测结果的不确定性.通过9个基准测试函数,对基于极坐标编码的果蝇优化算法进行仿真实验,结果表明了算法在收敛性和稳定性方面,优于其它5个优化算法,测试结果验证了极坐标编码方法的有效性和可行性.
Aiming at the disadvantage that Drosophila optimization algorithm is apt to fall into the premature convergence, the convergence speed is slow and the optimization accuracy is low, a Drosophila optimization algorithm based on polar coordinates encoding is proposed.In order to improve the optimization accuracy of Drosophila optimization algorithm, Form so as to increase the diversity of representation methods of a single parent’s optimal space and make the individuals in the population search randomly in the entire hypersphere of an individual to make the search scope of individuals more extensive.In the iterative optimization process, Degree and probability to adjust the polar angle, and gradually reduce the uncertainty of the observed results.From nine benchmark test functions, the simulation experiment of polar flies optimization algorithm based on polar coordinates is carried out. The results show that in the convergence and stability of the algorithm, Which is superior to the other five optimization algorithms. The test results verify the effectiveness and feasibility of the polar coordinate coding method.