Skip to main content
Log in

Opposition-based firefly algorithm for earth slope stability evaluation

  • Published:
China Ocean Engineering Aims and scope Submit manuscript

Abstract

This paper introduces a new approach of firefly algorithm based on opposition-based learning (OBFA) to enhance the global search ability of the original algorithm. The new algorithm employs opposition based learning concept to generate initial population and also updating agents’ positions. The proposed OBFA is applied for minimization of the factor of safety and search for critical failure surface in slope stability analysis. The numerical experiments demonstrate the effectiveness and robustness of the new algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Chen, Z. and Shao, C., 1988. Evaluation of minimum factor of safety in slope stability analysis, Can. Geotech. J., 25(4): 735–748.

    Article  Google Scholar 

  • Cheng, Y., 2003. Location of critical failure surface and some further studies on slope stability analysis, Comput. Geotech., 30(3): 255–267.

    Article  Google Scholar 

  • Cheng, Y., Li, L. and Chi, S., 2007. Performance studies on six heuristic global optimization methods in the location of critical slip surface, Comput. Geotech., 34(6): 462–484.

    Article  Google Scholar 

  • Cheng, Y., Li, L., Lansivaara, T., Chi, S. and Sun, Y., 2008. An improved harmony search minimization algorithm using different slip surface generation methods for slope stability analysis, Eng. Optim., 40(2): 95–115.

    Article  Google Scholar 

  • Greco, V. R., 1996. Efficient Monte Carlo technique for locating critical slip surface, J. Geotech. Eng., 122(7): 517–525.

    Article  Google Scholar 

  • Khajehzadeh, M., Taha, M. R. and El-Shafie, A., 2011. Reliability analysis of earth slopes using hybrid chaotic particle swarm optimization, J. Cent. South Univ. Technol., 18(5): 1626–1637.

    Article  Google Scholar 

  • Khajehzadeh, M., Taha, M. R., El-Shafie, A. and Eslami, M., 2012. A modified gravitational search algorithm for slope stability analysis, Eng. Appl. Artif. Intel., 25(8): 1589–1597.

    Article  Google Scholar 

  • Li, L. and Chu, X. S., 2011. An improved particle swarm optimization algorithm with harmony strategy for the location of critical slip surface of slopes, China Ocean Eng., 25(2): 357–364.

    Article  MathSciNet  Google Scholar 

  • Li, L., Yu, G. M., Chen, Z. Y. and Chu, X. S., 2010. Discontinuous flying particle swarm optimization algorithm and its application to slope stability analysis, J. Cent. South Univ. Technol., 17(4): 852–856.

    Article  Google Scholar 

  • Li, L., Cheng, Y. M. and Chu, X. S., 2013. A new approach to the determination of the critical slip surfaces of slopes, China Ocean Eng., 27(1): 51–64.

    Article  Google Scholar 

  • Li, S. J., Shangguan, Z., Duan, H., Liu, Y. and Luan, M., 2009. Searching for critical failure surface in slope stability analysis by using hybrid genetic algorithm, Geomech. Eng., 1(1): 85–96.

    Article  Google Scholar 

  • Morgenstern, N. R. and Price, V. E., 1965. The analysis of the stability of general slip surfaces, Geotechinque, 15(1): 79–93.

    Article  Google Scholar 

  • Spencer, E., 1967. A method of analysis of the stability of embankments assuming parallel inter-slice forces, Geotechnique, 17(1): 11–26.

    Article  Google Scholar 

  • Sun, J., Li, J. and Liu, Q., 2008. Search for critical slip surface in slope stability analysis by spline-based GA method, J. Geotech. Geoenviron. Eng., 134(2): 252–256.

    Article  Google Scholar 

  • Tizhoosh, H. R., 2005. Opposition-based learning: A new scheme for machine intelligence, Proceedings of the International Conference on Computational Intelligence for Modelling Control and Automation, Vienna, Austria.

    Google Scholar 

  • Yamagami, T. and Ueta, Y., 1988. Search for noncircular slip surfaces by the Morgenstern-Price method, Proceedings of the 6th International Conference on Numerical Methods in Geomechanics, 1335–1340.

    Google Scholar 

  • Yang, X. S., 2008. Nature-Inspired Metaheuristic Algorithms, Beckington, Luniver Press.

    Google Scholar 

  • Yang, X. S., 2009. Firefly algorithms for multimodal optimization, Lecture Notes in Computer Sciences, 5792, 169–178.

    Article  Google Scholar 

  • Zhang, K. and Cao, P., 2011. Modified electromagnetism-like algorithm and its application to slope stability analysis, J. Cent. South Univ. Technol., 18(6): 2100–2107.

    Article  Google Scholar 

  • Zhu, D., Lee, C., Qian, Q. and Chen, G., 2005. A concise algorithm for computing the factor of safety using the Morgenstern-Price method, Can. Geotech. J., 42(1): 272–278.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohammad Khajehzadeh.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khajehzadeh, M., Taha, M.R. & Eslami, M. Opposition-based firefly algorithm for earth slope stability evaluation. China Ocean Eng 28, 713–724 (2014). https://doi.org/10.1007/s13344-014-0055-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13344-014-0055-y

Key words

Navigation