改进鸽群算法求解高维复杂函数  

Improved Pigeon-inspired optimization Algorithm to Solve High Dimensional Complex Function

作　　者：姬小波 金景峰 李献锋 JI Xiaobo;JIN Jingfeng;LI Xianfeng(Chongqing Wangjiang Industry Co.,Ltd.,Chongqing 400071,China;Equipment Program Management Center,Army Armaments Division,Beijing 100072,China;The First Military Representative Room of Chongqing Region,Chongqing 400060,China)

机构地区：[1]重庆望江工业有限公司,重庆400071 [2]陆军装备部装备项目管理中心,北京100072 [3]重庆地区第一军事代表室,重庆400060

出　　处：《信息与电脑》2020年第24期44-47,共4页Information & Computer

摘　　要：本文针对鸽群算法在求解高维复杂函数时性能不佳的问题,提出了一种改进鸽群算法。将传统鸽群算法与Powell算法相结合,将每次迭代中的当前最优解通过Powell算法进行再次优化,能够提高鸽群算法的搜索能力和收敛速度。通过将改进后的算法与鸽群算法、粒子群算法进行了仿真对比实验,验证了改进算法性能的优越性。In this paper,an improved Pigeon-inspiredoptimization(PIO)algorithm is proposed to solve the problem of poor performance when solving high-dimensional complex functions.By combining the traditional PIO algorithm with Powell algorithm,the current optimal solution in each iteration is optimized again by Powell algorithm to improve the searching ability and convergence speed of PIO algorithm.Through four classical benchmark functions,the improved algorithm is compared with pigeon swarm algorithm and particle swarm algorithm,and the performance of the improved algorithm is verified.

关 键 词：鸽群算法 POWELL算法 高维复杂函数求解 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]