针对海马优化算法（seahorse optimization, SHO）存在的求解精度较低、容易早熟以及全局搜索能力不足等问题，设计了一种基于非线性惯性权重策略、改进的鲸鱼包围猎物策略以及改进的正余弦策略的多策略海马优化算法（multi-strategy seahorse optimization, MSHO）。首先，在SHO算法的运动行为中引入非线性惯性权重策略，以克服算法容易过早收敛的缺点；其次，将改进的鲸鱼包围猎物策略引入海马捕食成功的更新方程中，以降低算法陷入局部最优解的概率；然后，在算法的繁殖行为中引入改进的正余弦策略，以增强海马后代解的质量，进一步提升算法的全局寻优能力和稳定性。最后，为评估所提MSHO算法的性能，选取SHO算法，混沌的SHO算法、减法平均器算法、灰狼算法、海鸥算法、鲸鱼优化算法、粒子群算法与MSHO算法在23个基准测试函数上进行比较。实验结果表明，与其他7种算法相比，MSHO算法在20个函数上表现出更高的收敛精度，在16个函数上表现出更强的稳定性。此外，为检验MSHO算法在工程问题上的应用能力，将算法应用于求解焊接梁、悬臂梁和压力容器设计问题。实验结果表明，相较于其他7种不同算法，MSHO算法在这3类工程设计问题上表现出更好的搜索精度。

In order to solve the problems of SHO (seahorse optimization), such as low accuracy, precocity and insufficient global search ability. MSHO (multi-strategy seahorse optimization) algorithm based on nonlinear inertial weight strategy, improved whale encircling strategy and improved sine and cosine strategy was MSHO designed. Firstly, the nonlinear inertia weight was introduced into the motion behavior of SHO algorithm to overcome the shortcoming that the algorithm is prone to premature convergence. Secondly, the improved strategy of whale encircling prey was introduced into the updated equation of seahorse hunting success to reduce the probability of the algorithm falling into the local optimal solution. Then, the improved sine-cosine strategy was introduced into the reproduction behavior of the algorithm to enhance the quality of the hippocampal progeny solution, and further improve the global optimization ability and stability of the algorithm. Finally, in order to evaluate the performance of the proposed MSHO algorithm, SHO algorithm, chaotic SHO algorithm, subtraction average algorithm, gray Wolf algorithm, Seagull algorithm, whale optimization algorithm, particle swarm algorithm and MSHO algorithm were compared on 23 benchmark test functions. The experimental results show that MSHO algorithm shows higher convergence accuracy on 20 functions and stronger stability on 16 functions compared with other 7 algorithms. In addition, in order to test the application ability of MSHO algorithm in engineering problems, the algorithm is applied to solve the design problems of welded beams, cantilever beams and pressure vessels. The experimental results show that MSHO algorithm has better search accuracy in these three kinds of engineering design problems than other 7 different algorithms.