Abstract
The stability analysis of slope is an important and fundamental problem in geotechnical engineering, which is attracting the attention of many engineers and researchers. This paper proposes a dynamic biogeography-based optimization (BBO), to analyze slope stability problems. First, a real-world three-dimensional (3D) slope is described, and it is modeled as multiple two-dimensional (2D) slope planes, each of which is formulated as a single-objective optimization problem. Then a dynamic biogeography-based optimization algorithm, which is called DBBO, is developed by introducing change detection strategy into BBO. This strategy uses sentry solutions to detect their cost changes in different planes of a 3D slope, to reduce the unnecessary function evaluations. The proposed DBBO is applied to solve a case of classical 2D slope stability analysis and a case of 3D slope stability analysis with multiple planes established in this paper. The numerical results show that the proposed DBBO is a competitive algorithm for analyzing various slope stability problems, compared with other traditional methods.
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References
Wang, M., Liu, K., Yang, G., Xie, J.: Three-dimensional slope stability analysis using laser scanning and numerical simulation. J. Geomat. Nat. Haz. Risk. 8(2), 997–1011 (2017)
Li, Z., Yang, X.: Stability of 3D slope under steady unsaturated flow condition. J. Eng. Geol. 242, 150–159 (2018)
He, Y., Liu, Y., Zhang, Y., Yuan, R.: Stability assessment of three-dimensional slopes with cracks. J. Eng. Geol. 252, 136–144 (2019)
Singh, J., Banka, H., Verma, A.K.: A BBO-based algorithm for slope stability analysis by locating critical failure surface. J. Neural Comput. Appl. 31(2), 1–18 (2019)
Xu, J., Yang, X.: Seismic stability of 3D soil slope reinforced by geosynthetic with nonlinear failure criterion. J. Soil Dyn. Earth. Eng. 118, 86–97 (2019)
Khajehzadeh, M., Taha, M.R., Shafie, A., Eslami, M.: A modified gravitational search algorithm for slope stability analysis. J. Eng. Appl. Artif. Intel. 25, 1589–1597 (2012)
Kang, F., Li, J., Ma, Z.: An artificial bee colony algorithm for locating the critical slip surface in slope stability analysis. J. Eng. Optimiz. 45(2), 207–223 (2013)
Huang, S., Huang, M., Lyu, Y.: An improved KNN-based slope stability prediction model. J. Adv. Civil Eng. 8894109 (2020)
Raihan, T.M., Mohammad, K., Mahdiyeh, E.: A new hybrid algorithm for global optimization and slope stability evaluation. J. Central South Univ. 20, 3265–3273 (2013)
Gandomi, A.H., Kashani, A.R., Mousavi, M., Jalalvandi, M.: Slope stability analyzing using recent swarm intelligence techniques. Int. J. Numer. Anal. Met. 39(3), 295–309 (2015)
Chen, W., Zhao, Y., Liu, L., Wang, X.: A new evaluation method for slope stability based on TOPSIS and MCS. J. Adv. Civ. Eng. 1209470 (2020)
Song, L., et al.: Three-dimensional slope dynamic stability reliability assessment based on the probability density evolution method. J. Soil Dyn. Earth. Eng. 120, 360–368 (2019)
Koopialipoor, M., Armaghani, D.J., Hedayat, A., Marto, A.: Applying various hybrid intelligent systems to evaluate and predict slope stability under static and dynamic conditions. J. Soft Comput. 23, 5913–5929 (2018)
Liu, G., Zhuang, X., Cui, Z.: Three-dimensional slope stability analysis using independent cover based numerical manifold and vector method. J. Eng. Geol. 225, 83–95 (2017)
Ma, H.: An analysis of the equilibrium of migration models for biogeography-based optimization. J. Inform. Sci. 180(18), 3444–3464 (2010)
Simon, D.: Biogeography-based optimization. J. IEEE Trans. Evol. Comput. 12(6), 702–713 (2008)
Ma, H., Simon, D.: Analysis of migration models of biogeography-based optimization using markov theory. J. Eng. Appl. Artif. Intel. 24(6), 1052–1060 (2011)
Khajehzadeh, M., Taha, M., Eslami, M.: Opposition-based firefly algorithm for earth slope stability evaluation. J. China Ocean Eng. 28(5), 713–724 (2014)
Li, Y., Chen, Y., Zhan, T., Ling, D., Cleall, P.: An efficient approach for locating the critical slip surface in slope stability analyses using a real-coded genetic algorithm. J. Canadian Geotech. J. 47(7), 806–820 (2010)
Zhang, Z., Chai, J., Zhang, S., Qian, W.: Rearch on slope slide surface search based on differential evolution algorithm with mixed mutation strategy. J. Water Resour. Water Eng. 29 (4), 218--223 (2018)
Acknowledgments
This material was supported in part by the National Natural Science Foundation of China under Grant No. 52077213 and 62003332, and the Zhejiang Provincial Natural Science Foundation of China under Grant No. LY19F030011.
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Ma, H., Shan, Y., Sun, C., Fan, Y., Yang, Z. (2021). Multi-plane Slope Stability Analysis Based on Dynamic Evolutionary Optimization. In: Han, Q., McLoone, S., Peng, C., Zhang, B. (eds) Intelligent Equipment, Robots, and Vehicles. LSMS ICSEE 2021 2021. Communications in Computer and Information Science, vol 1469. Springer, Singapore. https://doi.org/10.1007/978-981-16-7213-2_10
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DOI: https://doi.org/10.1007/978-981-16-7213-2_10
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