Applications of Particle Swarm Optimization in Geotechnical Engineering: A Comprehensive Review
| Autor: | Mohsen Hajihassani, Roohollah Kalatehjari, D. Jahed Armaghani |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
education.field_of_study
Engineering business.industry Population MathematicsofComputing_NUMERICALANALYSIS 0211 other engineering and technologies Soil Science Particle swarm optimization Geology 02 engineering and technology Foundation engineering 010502 geochemistry & geophysics Geotechnical Engineering and Engineering Geology 01 natural sciences Evolutionary computation Engineering optimization Slope stability Architecture Geotechnical engineering education business Slope stability analysis Soil mechanics 021101 geological & geomatics engineering 0105 earth and related environmental sciences |
| Zdroj: | Geotechnical and Geological Engineering. 36:705-722 |
| ISSN: | 1573-1529 0960-3182 |
| DOI: | 10.1007/s10706-017-0356-z |
| Popis: | Particle swarm optimization (PSO) is an evolutionary computation approach to solve nonlinear global optimization problems. The PSO idea was made based on simulation of a simplified social system, the graceful but unpredictable choreography of birds flock. This system is initialized with a population of random solutions that are updated during iterations. Over the last few years, PSO has been extensively applied in various geotechnical engineering aspects such as slope stability analysis, pile and foundation engineering, rock and soil mechanics, and tunneling and underground space design. A review on the literature shows that PSO has utilized more widely in geotechnical engineering compared with other civil engineering disciplines. This is due to comprehensive uncertainty and complexity of problems in geotechnical engineering which can be solved by using the PSO abilities in solving the complex and multi-dimensional problems. This paper provides a comprehensive review on the applicability, advantages and limitation of PSO in different disciplines of geotechnical engineering to provide an insight to an alternative and superior optimization method compared with the conventional optimization techniques for geotechnical engineers. |
| Databáze: | OpenAIRE |
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