融合莱维飞行与黄金正弦的蚁狮优化算法

针对蚁狮优化算法较易陷入局部最优停滞、收敛精度低以及收敛速度较慢等问题，将莱维飞行机制和黄金正弦算法融合到蚁狮优化算法中，提出了融合莱维飞行与黄金正弦的蚁狮优化算法（LGSALO）。该算法利用 Levy 飞行的变异机制对寻优过程中位置更新方式进行变异操作，可以改善种群多样性，使得算法跳出局部最优，提高全局寻优能力，并在一定程度上避免了算法的过早收敛；同时引入黄金正弦算法改进精英蚁狮的寻优方式，协调算法的全局探索与局部开发能力。实验仿真结果表明，该改进算法的寻优性能良好，开发能力强。

Ant lion optimization algorithm integrating with Levy flight and golden sine

To solve the problem that the ant lion optimization algorithm was prone to local optimal stagnation, low convergence accuracy and slow convergence speed, this paper proposed the ant lion optimization algorithm integrating with levy flight and golden sinusoids(LGSALO). This algorithm used the variation mechanism of Levy flight to carry out mutation operation on the position update mode in the optimization process, which could improve the population diversity, make the algorithm jump out of the local optimum, improve the global optimization ability, and avoid the premature convergence of the algorithm to some extent. At the same time, the algorithm introduced the golden sine algorithm to improve the optimization mode of the elite ant lion and coordinate the ability of global exploration and local development. The experimental simulation results show that the improved algorithm has good performance of optimization and strong development ability.