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Particle Swarm Optimization Variants for Solving Geotechnical Problems: Review and Comparative Analysis

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Abstract

Optimization techniques have drawn much attention for solving geotechnical engineering problems in recent years. Particle swarm optimization (PSO) is one of the most widely used population-based optimizers with a wide range of applications. In this paper, we first provide a detailed review of applications of PSO on different geotechnical problems. Then, we present a comprehensive computational study using several variants of PSO to solve three specific geotechnical engineering benchmark problems: the retaining wall, shallow footing, and slope stability. Through the computational study, we aim to better understand the algorithm behavior, in particular on how to balance exploratory and exploitative mechanisms in these PSO variants. Experimental results show that, although there is no universal strategy to enhance the performance of PSO for all the problems tackled, accuracies for most of the PSO variants are significantly higher compared to the original PSO in a majority of cases.

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Authors and Affiliations

  1. Department of Civil Engineering, University of Memphis, Memphis, TN, 38152, USA

    Ali R. Kashani

  2. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, 2308, Australia

    Raymond Chiong

  3. Centre for Artificial Intelligence Research and Optimisation, Torrens University Australia, Fortitude Valley, Brisbane, QLD, 4006, Australia

    Seyedali Mirjalili

  4. Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, 2007, Australia

    Amir H. Gandomi

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  1. Ali R. Kashani
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Kashani, A.R., Chiong, R., Mirjalili, S. et al. Particle Swarm Optimization Variants for Solving Geotechnical Problems: Review and Comparative Analysis. Arch Computat Methods Eng 28, 1871–1927 (2021). https://doi.org/10.1007/s11831-020-09442-0

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