多交互式人工蜂群算法及其收敛性分析

发布时间：2018-03-30 12:06

本文选题：人工蜂群算法　切入点：跨维度搜索策略　出处：《计算机应用》2017年03期

【摘要】：针对人工蜂群(ABC)算法不易跳出局部最优解的缺点,提出了多交互式人工蜂群(MIABC)算法。该算法在基本人工蜂群算法的基础上引入随机邻域搜索策略,结合跨维搜索策略,且改进蜜蜂越限处理方式,使得算法搜索方式多样化,从而使得算法搜索更具跳跃性,不易陷入局部最优解,同时,对其进行收敛性分析和性能测试。在五种经典基准测试函数和时间复杂度实验上的仿真结果表明,相对于标准人工蜂群算法和基本粒子群优化(PSO)算法,该算法在1E-2精度下收敛速度提高了约30%和65%,搜索精度更优,且在高维求解问题方面有明显优势。
[Abstract]:In view of the disadvantage of artificial bee colony (ABC) algorithm which is not easy to jump out of the local optimal solution, a multi-interactive artificial bee colony MIABC algorithm is proposed. Based on the basic artificial bee colony algorithm, the random neighborhood search strategy is introduced, and the cross-dimensional search strategy is combined. And improve the bee beyond the limit processing way, make the algorithm search way diversification, so that the algorithm search more jumping, not easy to fall into the local optimal solution, at the same time, The simulation results of five classical benchmark functions and time complexity experiments show that compared with the standard artificial bee colony algorithm and the basic particle swarm optimization (PSO) algorithm, The convergence speed of the algorithm is improved by about 30% and 65% under 1E-2 precision, the search accuracy is better, and the algorithm has obvious advantages in solving problems in high dimension.
【作者单位】：上海电机学院电气学院;
【基金】：上海市教委科研创新项目(13YZ140)~~
【分类号】：TP18

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