Calculating the minimum slope safety factor or locating the critical slip surface of a soil slope is a complex optimization problem. This paper describes an improved whale optimization algorithm (IWOA) for locating the critical slip surface of a soil slope. Locating a critical slip surface is transformed into a three-dimensional problem from a high-dimensional optimization. Combined with the Morgenstern–Price method, IWOA is compared against other optimization techniques in an experimental study. Test results using 13 benchmark functions show that IWOA significantly outperforms the conventional whale optimization algorithm (WOA) and particle swarm optimization (PSO). The IWOA method is then used to search for the critical slip surfaces of four slopes. The results show that IWOA again performs better than WOA and PSO in locating the critical slip surface.

计算最小边坡安全系数或确定土质边坡的临界滑动面是一个复杂的优化问题。本文介绍了一种用于定位土质边坡临界滑动面的改进的鲸鱼优化算法（IWOA）。定位关键滑动表面会从高维优化转换为三维问题。在实验研究中，结合了Morgenstern–Price方法，将IWOA与其他优化技术进行了比较。使用13个基准函数的测试结果表明，IWOA明显优于传统的鲸鱼优化算法（WOA）和粒子群优化（PSO）。然后使用IWOA方法搜索四个斜坡的临界滑动面。