Abstract
Generally, each optimization technique has its advantages and drawbacks, which means that not all optimization problems can be effectively solved by a given optimization method.
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References
Zentar R, Hicher P, Moulin G (2001) Identification of soil parameters by inverse analysis. Comput Geotech 28(2):129–144
Papon A, Riou Y, Dano C, Hicher PY (2012) Single-and multi-objective genetic algorithm optimization for identifying soil parameters. Int J Numer Anal Methods Geomech 36(5):597–618
Calvello M, Finno RJ (2004) Selecting parameters to optimize in model calibration by inverse analysis. Comput Geotech 31(5):410–424
Finno RJ, Calvello M (2005) Supported excavations: observational method and inverse modeling. J Geotech Geoenviron Eng 131(7):826–836
Hill MC (1998) Methods and guidelines for effective model calibration: US geological survey denver. CO, USA
Wheeler SJ, Näätänen A, Karstunen M, Lojander M (2003) An anisotropic elastoplastic model for soft clays. Can Geotech J 40(2):403–418
Yin Z-Y, Jin Y-F, Shen JS, Hicher P-Y (2018) Optimization techniques for identifying soil parameters in geotechnical engineering: comparative study and enhancement. Int J Numer Anal Methods Geomech 42(1):70–94
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© 2019 Springer Nature Singapore Pte Ltd. and Tongji University Press
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Yin, ZY., Jin, YF. (2019). Comparative Study of Typical Optimization Methods. In: Practice of Optimisation Theory in Geotechnical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-3408-5_3
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DOI: https://doi.org/10.1007/978-981-13-3408-5_3
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Online ISBN: 978-981-13-3408-5
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