改进布谷鸟算法在边坡滑面搜索中的应用

根据布谷鸟算法前期搜索随机跳跃性大、后期搜索收敛速度慢的缺点，引入惯性权重并结合局部蒙特卡罗优化，得到改进的布谷鸟算法，其搜索结果与Spencer法、瑞典条分法进行对比可知，不论滑面的位置还是安全系数都很相近。与退火模拟算法对比验证其可靠度，结果表明:改进的布谷鸟算法更优秀，得到的结果更精确，可以应用于边坡滑面搜索。

Application of Improved Cuckoo Search in Slip Surface Search

Because cuckoo search algorithm has defects, presenting random big leap in prophase search and slow convergence in late search, inertia weight combined with local Monte-Carlo optimization was introduced to improve cuckoo search. The search results, no matter the sliding surface position or the safety factor, were very close to those from Spencer method or Sweden slices method. Furthermore, its reliability was verified by simulated annealing algorithm. The result shows that the improved CS algorithm is better with more accurate solution, thus can be applied to search slip surface of slope.