混沌精英质心拉伸机制的樽海鞘群算法

针对樽海鞘群算法求解精度不高的缺点，提出一种混沌精英质心拉伸机制的樽海鞘群算法。引入改进的Tent混沌序列生成初始种群，以增加初始个体的多样性；选择最优个体采用精英质心拉伸机制，可增强全局搜索能力。将改进算法在12个典型复杂函数和CEC2014函数优化问题上进行仿真实验，并同经典的遗传算法和粒子群算法进行对比。结果表明，混沌精英质心拉伸机制的樽海鞘群算法具有更好的全局搜索能力，寻优精度比标准算法有所增强。在求解高维和多峰测试函数上，改进算法拥有更好的性能。

Salp Swarm Algorithm Using Chaotic and Elite Centroid Stretching Mechanism

In order to solve the problem that the standard Salp Swarm Algorithm（SSA） has low result precision in the evolutionary process, an improved algorithm called Chaotic and Elite centroid stretching mechanism Salp Swarm Algorithm（CESSA） is proposed. The improved Tent chaotic sequence is used to initiate the individuals’ position, which can strengthen the diversity of initiate individuals. Then the elite centroid stretching mechanism is applied to the current elite individuals, which can enhance global searching ability of the proposed CESSA algorithm. The improved algorithm is simulated on 12 typical complex functions and CEC2014 function optimization problems, and compared with two classical intelligent algorithms, genetic algorithm and particle swarm optimization algorithm. The results show that the CESSA has better global searching ability, and meanwhile, the optimization accuracy is also enhanced than the standard algorithm. Especially, in solving the high-dimension and multimodal function optimization problem, the improved algorithm has better performance.