具有自适应边界与最优引导的莱维飞行蚁狮优化算法

Levy Flight Ant Lion Optimizer with Adaptive Boundary and Optimal Guidance

针对蚁狮算法存在探索与开发能力不平衡的缺点,提出了具有自适应边界与最优引导的莱维飞行改进算法.首先蚁狮调整边界范围,蚂蚁做莱维飞行,以此平衡探索与开发能力;其次较差蚁狮做高斯变异,并通过自适应最优引导方程,提高收敛速度和全局搜索能力.6个标准测试函数的仿真结果表明,相比其它算法,提出的改进算法提高了最优解的精度和收敛速度.

Aiming at the shortcoming that the ant-lion algorithm has unbalanced exploration and development capability,an improved levy flight algorithm with adaptive boundary and optimal guidance is proposed.First,the ant lion to adjust the scope of the border,ants do levy flight,in order to balance the exploration and development capabilities.Second,the worse Ant lion do Gaussian mutation,and through the adaptive best-guided equation,to improve the convergence speed and global search ability.The simulation results of six standard test functions show that the improved algorithm improves the accuracy and convergence speed of the optimal solution compared with other algorithms.