多子群改进的海洋捕食者算法

Improved marine predators algorithm with multi-subpopulation

文章针对海洋捕食者算法(Marine Predators Algorithm,MPA)求解精度不高和收敛速度慢等缺点,提出一种多子群改进的海洋捕食者算法(Multi-subpopulation Marine Predators Algorithm,MSMPA).根据不同适应度值将海洋捕食者种群分为领导者、追随者和衔尾者三个子群.领导者子群保持位置不变,追随者子群进行高斯变异,衔尾者子群由全局最优位置和平均位置矢量生成.使用不同维度的经典基准函数来评估改进海洋捕食者算法的效率.实验结果显示,经过改进的海洋捕食者算法拥有更高的寻优精度和稳定性.

Aiming at the shortcomings of the marine predator algorithm,such as low accuracy and slow convergence,a multi-subgroup improved marine predator algorithm is proposed.According to different fitness values,the marine predator population is divided into three subgroups:leader,follower and tailer.The leader subgroup keeps its position unchanged,the follower subgroup undergoes Gaussian mutation,and the tail subgroup is generated by the global optimal position and the average position vector.Classical benchmark functions of different dimensions are used to evaluate the efficiency of the improved marine predator algorithm.The results show that the improved marine predator algorithm has better optimization accuracy and stability.