Locating critical slip surfaces of soil slopes with heuristic algorithms: A comparative study

Calculating the minimum safety factor for locating or investigating the critical slip surfaces of soil slopes is a complex optimization problem. In this work, a series of variables are utilized to represent the slip surfaces of the slope, and the Morgenstern and Price's method is used to calculate the safety factor of a given slip surface. The performances of eight heuristic optimization algorithms (grey wolf optimizer, particle swarm optimization algorithm, whale optimization algorithm, salp swarm algorithm, multi-verse optimizer, ant lion optimizer, cuckoo search algorithm, and equilibrium optimizer) for locating the critical slip surfaces of slopes are compared. Three cases (one homogeneous slope and two multi-layered slopes) show that the equilibrium optimizer is superior to the other algorithms in terms of the quality of the solution, the convergence rate, and the robustness. One should carefully use the salp swarm algorithm and ant lion optimizer to locate the critical slip surfaces of slopes.