Numerical Comparison of the Performance of Genetic Algorithm and Particle Swarm Optimization in Excavations

Seyyed Mohammad Hashemi, Iraj Rahmani


Today, the back analysis methods are known as reliable and effective approaches for estimating the soil strength parameters in the site of project. The back analysis can be performed by genetic algorithm and particle swarm optimization in the form of an optimization process. In this paper, the back analysis is carried out using genetic algorithm and particle swarm optimization in order to determine the soil strength parameters in an excavation project in Tehran city. The process is automatically accomplished by linking between MATLAB and Abaqus software using Python programming language. To assess the results of numerical method, this method is initially compared with the results of numerical studies by Babu and Singh. After the verification of numerical results, the values of the three parameters of elastic modulus, cohesion and friction angle (parameters of the Mohr–Coulomb model) of the soil are determined and optimized for three soil layers of the project site using genetic algorithm and particle swarm optimization. The results optimized by genetic algorithm and particle swarm optimization show a decrease of 72.1% and 62.4% in displacement differences in the results of project monitoring and numerical analysis, respectively. This research shows the better performance of genetic algorithm than particle swarm optimization in minimization of error and faster success in achieving termination conditions.


Back Analysis; Soil Strength Parameters; Genetic Algorithm; Particle Swarm Optimization; Python; Excavation.


Rechea, C., S. Levasseur, and R. Finno. “Inverse Analysis Techniques for Parameter Identification in Simulation of Excavation Support Systems.” Computers and Geotechnics 35, no. 3 (May 2008): 331–345. doi:10.1016/j.compgeo.2007.08.008.

Dehghan, A., F. Rezaee, and A. Ghanbari, “Back analysis of Karaj metro tunnel to determine geomechanical parameters of the encompassing soil.” Geological Engineering Journal, No.2 (2009).

Sakurai, Shunsuke, Shinichi Akutagawa, Kunifumi Takeuchi, Masato Shinji, and Norikazu Shimizu. “Back Analysis for Tunnel Engineering as a Modern Observational Method.” Tunnelling and Underground Space Technology 18, no. 2–3 (April 2003): 185–196. doi:10.1016/s0886-7798(03)00026-9.

Pourbanaee, S. “Back analysis of the behavior of tied walls using numerical modeling and monitoring results”, Master thesis (2013).

Eshghi, Kourosh, and Mehdi Kariminasab. “An analysis of metaheuristic algorithms and design methods”, 1st edition, Tehran: Sharif University of Technology Publications, (2016).

Holland, J. "Adaptation in natural and artificial systems: an introductory analysis with application to biology." Control and artificial intelligence, (1975).

Vahdati, Pooya, Séverine Levasseur, Hans Mattsson, and Sven Knutsson. "Inverse soil parameter identification of an earth and rockfill dam by genetic algorithm optimization." In ICOLD European Club Symposium: doi:10/04/2013-12/04/2013. 2013.

Levasseur, S., Y. Malécot, M. Boulon, and E. Flavigny. “Soil Parameter Identification Using a Genetic Algorithm.” International Journal for Numerical and Analytical Methods in Geomechanics 32, no. 2 (2008): 189–213. doi:10.1002/nag.614.

Goldberg, DE. “Algorithmes Genetiques: Exploration, Optimisation et Apprentissage Automatique. Adisson-Wesley: Reading, MA, (1991).

Pal, Surajit, G. Wije Wathugala, and Sukhamay Kundu. “Calibration of a Constitutive Model Using Genetic Algorithms.” Computers and Geotechnics 19, no. 4 (January 1996): 325–348. doi:10.1016/s0266-352x(96)00006-7.

Bullnheimer, Bernd, Richard F. Hartl, and Christine Strauss. "A new rank based version of the Ant System. A computational study." (1997).

Dorigo, M., V. Maniezzo, and A. Colorni. “Ant System: Optimization by a Colony of Cooperating Agents.” IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 26, no. 1 (1996): 29–41. doi:10.1109/3477.484436.

Olariu, Stephan, and Albert Zomaya, eds. “Handbook of Bioinspired Algorithms and Applications.” Chapman & Hall/CRC Computer & Information Science Series (September 29, 2005). doi:10.1201/9781420035063.

Hashemi, S. M. “Back analysis of soil strength parameters by genetic algorithms”, Master thesis (2017).

Tang, Yu-Geng, and Gordon Tung-Chin Kung. “Application of Nonlinear Optimization Technique to Back Analyses of Deep Excavation.” Computers and Geotechnics 36, no. 1–2 (January 2009): 276–290. doi: 10.1016/j.compgeo.2008.02.004.

Kia, S. M. “Genetic algorithms in MATLAB”, 3rd edition, Tehran: Kian Academic Publications (2012).

Alireza, Mahdi. “Genetic algorithms and their applications”, 3rd edition, Tehran: Naqous Andisheh publisher (2008).

Singh, Vikas Pratap, and G. L. Sivakumar Babu. “2D Numerical Simulations of Soil Nail Walls.” Geotechnical and Geological Engineering 28, no. 4 (December 25, 2009): 299–309. doi:10.1007/s10706-009-9292-x.

Razavi, Seyyed Kazem, and Masoud Hajialilue Bonab. “Study of Soil Nailed Wall Under Service Loading Condition.” Proceedings of the Institution of Civil Engineers - Geotechnical Engineering 170, no. 2 (April 2017): 161–174. doi:10.1680/jgeen.16.00006.

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DOI: 10.28991/cej-03091149


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