【摘要】 为了提升樽海鞘群(Salp Swarm Algorithm, SSA)算法的求解精度和全局搜索能力,提出了一种基于正态过程搜索和差分进化(Differential Evolution, DE)算法的改进樽海鞘群算法——双领导者樽海鞘群算法(Two Types of Leaders Salp Swarm Algorithm, TTLSSA)。该算法设置了两类领导者和两种跟随群体,其中执行正态过程搜索的领导者需要进行正态过程游走、交叉、选择等操作,主要用于全局勘探;当前最优解附近的领导者在随迭代次数呈锯齿状变化的参数gap的影响下,兼顾了全局搜索和局部开发两种功能。用18个不同类型的标准测试函数检验所提算法的性能,并与DE、SSA、正弦余弦算法(Sines and Cosines Algorithm, SCA)、灰狼优化(Grey Wolf Optimizer, GWO)算法以及鲸鱼优化算法(Whale Optimization Algorithm, WOA)做对比,TTLSSA在16个测试函数上的平均精度排名第1或并列第1,在2个测试函数上的平均精度排名第2,在6种算法中平均耗时排名第2,说明了TTLSSA在没有增加SSA时间成本的前提下,显著提升了优化能力。更多还原

【Abstract】 In order to improve the solution accuracy and global search capability of Salp swarm algorithm(SSA),an improved Salp swarm algorithm based on normal process search and differential evolution algorithm is proposed, called two types of leaders salp swarm algorithm(TTLSSA).Two types of leaders and two following groups are set up in the algorithm.Among them, the leader performing normal process search needs to carry out normal process migration, crossover, selection and other operations, which are mainly used for global exploration.Under the influence of the gap parameter, which varies with the number of iterations, the leader near the current optimal solution combines both global search and local development functions.Eighteen different types of standard test functions are used to test the performance of the proposed algorithm, compared with DE,SSA,sines and cosines algorithm(SCA),grey wolf optimizer(GWO),and whale optimization algorithm(WOA).TTLSSA ranks the first or joint first in the average precision of 16 test functions, the second in the average precision of 2 test functions, and the second in the ave-rage time of 6 algorithms, indicating that TTLSSA significantly improves the optimization ability without increasing the time cost of SSA.更多还原