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

Ali R. Kashani, Raymond Chiong, Seyedali Mirjalili, Amir H. Gandomi

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
JournalArchives of Computational Methods in Engineering
DOIs
Publication statusAccepted/In press - 2020

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