一种全局搜索策略的鲸鱼优化算法  

Whale Optimization Algorithm with Global Search Strategy

作　　者：刘磊 白克强[1] 但志宏 张松 刘知贵[1,3] LIU Lei;BAI Ke-qiang;DAN Zhi-hong;ZHANG Song;LIU Zhi-gui(Scholl of Information Engineering,SWUST,Mianyang 621000,China;AECC Sichuan Gas Turbine Establishment,Mianyang 621703,China;School of Computer Science and Technology,SWUST,Mianyang 621000,China)

机构地区：[1]西南科技大学信息工程学院,四川绵阳621000 [2]中国航发四川燃气涡轮研究院,四川绵阳621703 [3]西南科技大学计算机科学与技术学院,四川绵阳621000

出　　处：《小型微型计算机系统》2020年第9期1820-1825,共6页Journal of Chinese Computer Systems

基　　金：四川省科技计划项目(18ZDYF3046)资助;西南科技大学研究生创新基金项目(19ycx0110)资助;中国航发四川燃气涡轮研究院科研基金项目(SHYS-2019-0004)资助。

摘　　要：针对标准鲸鱼优化算法全局搜索能力不足、收敛速度慢等问题,提出一种全局搜索策略的鲸鱼优化算法.在鲸鱼位置更新公式中加入自适应权重,动态调节最优位置的影响力,改善算法收敛速度;使用变螺旋位置更新策略,动态调整螺旋的形状,提升算法全局搜寻能力;引入最优邻域扰动策略,避免算法陷入局部最优解,解决算法早熟现象.在11个标准测试函数上进行仿真实验,结果表明改进后的鲸鱼优化算法相较其余优化算法,具有更高的寻优精度和更快的收敛速度,证明了改进策略的有效性.Aiming at the problem that the traditional whale optimization algorithm has the disadvantage of global search ability and slow convergence speed,a whale optimization algorithm with global search strategy is proposed.Add adaptive weight to the whale position update formula,dynamically adjust the influence of the optimal position,and improve the algorithm′s convergence rate;The algorithm introduces variable spiral position update strategy to dynamically adjust the spiral shape,which strengthens the global search ability of the algorithm;introduce the optimal neighborhood disturbance strategy to avoid the algorithm falling into the local optimum,solve the premature convergence of the algorithm.The paper uses eleven test function optimization problems for simulation experiments.The results show that the improved whale optimization algorithm has higher optimization accuracy and faster convergence rate than other optimization algorithm,which proves the effectiveness of the improved strategy.

关 键 词：鲸鱼优化算法 自适应权重 全局搜索 最优邻域 测试函数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]