Optimization of Geotechnical Parameters Used in Slope Stability Analysis by Metaheuristic Algorithms

Abstract

Quick development of computer execution empowers new improvements in the field of geotechnical engineering and related zones. Considering design variables, constraints, and objectives in any complex problem, conventional optimization techniques are usually inadequate to find the best solution. So, to overcome these problems, many metaheuristic optimization methods are applied successfully. In this paper, study has been performed to use different methods (DE, BOA, SCA, and PSO) to find the solution of civil engineering problem, i.e., slope stability analysis. Slope stability can be defined as resistance of an inclined soil to withstand or undergo the movement. It is crucial because failure of slope may lead to loss of life, economy, and property. Stability of slopes involves such complexity in case of their different geotechnical parameters. In this paper, different metaheuristic algorithms have been used for optimization of factor of safety and other related parameters of slope stability analysis.

A Bio-Inspired Multi-Population-Based Adaptive Backtracking Search Algorithm

“…For example, Saha et al [ 17 ] applied the HSOS algorithm on the pseudo-dynamic-bearing capacity of shallow strip footing; the critical failure mechanisms were determined via optimization with a genetic algorithm (GA). Different bio-inspired algorithms have been used to optimize the factor of safety and other related parameters of slope stability analysis in [ 18 ]. The weight and cost of the cantilever retaining wall have been minimized using a hybrid algorithm, namely, h-BOASOS in [ 19 ].…”