Civil Engineering and Architecture Vol. 13(3A), pp. 2370 - 2381
DOI: 10.13189/cea.2025.131315
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Metaheuristic Optimization for Earthquake Stability of Retaining Walls Structures Using Evolutionary Algorithms

Mouna El Mkhalet ^*, Hicham Lamouri , Nouzha Lamdouar
Civil Engineering and Construction Research Structure Laboratory GCC, Mohammadia School of Engineers, Mohammed V University in Rabat, Morocco

ABSTRACT

Bio-inspired algorithms have emerged as efficient techniques for structural optimization, offering robust solutions to complex engineering problems. This study begins with a review of research conducted by various authors on the optimization of retaining walls. It includes a literature survey of three evolutionary algorithms, PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization), and SA (Simulated Annealing) detailing their principles, current applications, and associated calculation steps. The case study focuses on optimizing the structural configuration of a retaining wall, incorporating dynamic analysis using the Mononobe-Okabe approach to evaluate seismic stability. In this context, the objective function, based on surface area, is considered alongside constraints related to sliding, overturning, and geometric requirements of a retaining wall under seismic conditions. The fifth section of this study presents the performance analysis, confirming that PSO is the fastest and most stable algorithm, while SA is the slowest. Additionally, sensitivity analysis highlights PSO's efficiency in achieving low surface values, and Sobol's indices identify X₂ and X₄ as the most influential variables. The final part of the study is dedicated to the discussion of results, divided into three sections. The first section compares the results obtained by the three algorithms in terms of structural gains, highlighting PSO and ACO as the most effective. Next, a performance analysis reveals that ACO emerges as the most efficient algorithm overall. Finally, the optimal dimensions of the retaining wall in both static and dynamic modes are compared, showing nearly identical results and prompting interesting questions. The main contribution of this work lies in the first-time application of a scientific, metaheuristic, and multi-objective optimization model to solve an optimization problem for a cantilever retaining wall. This approach determines the optimal dimensions under seismic conditions, adhering to the Moroccan RPS 2011 guidelines.

KEYWORDS
Genetic Algorithms, Particle Swarm Optimization, Ant Colony Optimization, Simulated Annealing, Retaining Walls, Mononobe Okabe Approach, Structural Stability, RPS 2011

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Mouna El Mkhalet , Hicham Lamouri , Nouzha Lamdouar , "Metaheuristic Optimization for Earthquake Stability of Retaining Walls Structures Using Evolutionary Algorithms," Civil Engineering and Architecture, Vol. 13, No. 3A, pp. 2370 - 2381, 2025. DOI: 10.13189/cea.2025.131315.

(b). APA Format:
Mouna El Mkhalet , Hicham Lamouri , Nouzha Lamdouar (2025). Metaheuristic Optimization for Earthquake Stability of Retaining Walls Structures Using Evolutionary Algorithms. Civil Engineering and Architecture, 13(3A), 2370 - 2381. DOI: 10.13189/cea.2025.131315.