基于天体运动更新机制的改进樽海鞘群算法

An Astrophysics-inspired Salp Swarm Algorithm

为了解决樽海鞘群算法(SSA)在收敛速度和求解精度方面存在的问题,提出了一种改进的樽海鞘群算法。通过在原算法中引入天体运动更新机制来提高算法的收敛速度和收敛精度。用7个常见的测试函数对改进算法进行仿真验证,同时将结果与现有的灰狼算法(GWO)、粒子群算法(PSO)和蚁狮算法(ALO)进行对比。结果表明,引入天体运动更新机制的樽海鞘群算法具有更优的性能,证明了改进方案的有效性。

In order to make up for the shortcomings such as the salp swarm algorithm in the convergence speed and the low accuracy of the solution,an improved salp swarm algorithm is proposed.The convergence speed and convergence precision of the algorithm are increased by introducing the celestial motion update mechanism on the original algorithm.The improved algorithm is verified by seven common test functions,and the results are compared with the existing gray wolf algorithm,particle swarm optimization and ant lion algorithm.The results show that the salp swarm algorithm with celestial motion update mechanism has better performance and proves the superiority of the improved scheme.