Application of optimization algorithms in geotechnical engineering as decision-making support tool
Application of optimization algorithms in geotechnical engineering as decision-making support tool
This paper advocates for climate-responsive optimization in civil engineering, leveraging the NSGA-II algorithm. Conducting an in-depth study on a dike structure, the integration of pymoo with Plaxis 2023.2 via Python emerges as a potent decision support tool. Employing a plane strain approach with 15-noded triangular elements, the numerical model undergoes SRFEA for stability assessment. Three objectives, material demand (f1), LC2 exploitation (f2), and LC3 exploitation (f3), are systematically minimized by NSGA-II. Results, depicted in a Pareto surface, spotlight a wider spread for material demand, emphasizing its variability. Findings underscore the pivotal role of multi-objective algorithms in guiding sustainable civil engineering decisions amid climate change challenges.
Kacper Cerek; Elnaz Hadjiloo; Jurgen Grabe
18th European Conference on Soil Mechanics and Geotechnical Engineering (ECSMGE2024)
A - New developments on structural design
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