Slope stability analysis using recent metaheuristic techniques: a comprehensive survey

Abstract

In the framework of designing civil engineering structures such as dams and road embankments, slope stability assessment is essential. Many slope stability assessment methods based on swarm intelligence algorithms and artificial intelligence techniques have been developed in the past decade. Therefore, this paper aims to provide an up-to-date overview of slope stability by summarizing the review of applications of several metaheuristics in this field with their advantages and limitations. In this study, we present recent swarm intelligence methods and machine learning techniques used for assessing the stability of slopes and compare them with the antlion optimiser (ALO) technique. The factor of safety related to every slip surface searched was computed using Morgenstern-Price method. The performance of the proposed ALO is evaluated and validated for four slope examples against recent metaheuristics. Finally, the work carried out will help practitioners as they can now have all swarm intelligence approaches combined in one paper and will help in choosing them the right technique based on their application.