FANPCE technique for risk assessment on subway station construction
Abstract
Risk assessment is critical for the construction of the subway station to improve the risk management and reduce the additional loss. According to field investigation of safe construction, the analytical network process (ANP), fuzzy set theory and fuzzy comprehensive evaluation (FCE), a fuzzy ANP comprehensive evaluation (FANPCE) model was proposed to evaluate the risk of subway station construction in this paper. Twelve key risk factors of subway station construction were identified through literature review and questionnaires. The interdependency among risk factors were illustrated through the network structure of ANP, and then a weight matrix of single risk factors was built by comments and survey results, and the interdependent weight matrix was quantified by integrating the triangular fuzzy number into the ANP. Subsequently, the total risk rank of assessed projects can be quantified though the synthesis of weight matrices with the synthetic operator of FCE. Wu Lu Kou subway station was selected as a case study. The results imply that, construction experience, underground water, and safety consciousness have a substantial influence on construction projects and that the total construction risk of Wu Lu Kou subway station is ranked at I level. Moreover, the loss analysis of the whole construction process verifies this method. This research contributes to developing a FANPCE method to identify the risk factors with high weights, assess the risk rank of projects and appropriately respond to the results. In addition, the developed fuzzy set theory-ANP-FCE integrated network provides stakeholders a consolidated model for the risk evaluation.
Keyword : construction risk, subway station, risk identification, ANP, risk assessment, FANPCE method
How to Cite
Wu, L., Bai, H., Yuan, C., & Xu, C. (2019). FANPCE technique for risk assessment on subway station construction. Journal of Civil Engineering and Management, 25(6), 599-616. https://doi.org/10.3846/jcem.2019.10373
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Guo, Z., Shang, X. L., & Li, H. (2011). AHP-based safety assessment model for rail transit system. China Railway Science, 32(3), 123-125.
Hu, Q. F., & Qin, J. B. (2013). Statistical analysis on accidents of subway tunnel construction from 2003 to 2011 in China. Chinese Journal of Underground Space and Engineering, 9(3), 705-710.
Jie, Y. X., Hu, T., Li, Q. Y., & Li, G. X. (2004). Application of analytical hierarchy process in the comprehensive safety assessment system of Yangtze River levee. Journal of Tsinghua University (Science and Technology), 44(12), 634-1637.
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Li, F. W., Du, X. L, Zhang, M. J., & Gao, Y. H. (2009). Application of improved AHP in risk identification during open-cut construction of a subway station. Journal of Beijing University of Technology, 38(2), 167-172.
Li, F. W., Du, X. L., & Zhang, M. J. (2014). Statistical analysis of accidents in metro construction. Chinese Journal of Underground Space and Engineering, 10(2), 474-479.
Li, H. R., Li, Q. M., & Lu, Y. (2017). Statistical analysis on regularity of subway construction accidents from 2002 to 2016 in China. Urban Rapid Rail Transit, 30(1), 12-19.
Li, X. B., Feng, F., Li, D. Y., Du, K., Ranjith, P. G., & Rostami, J. (2018). Failure characteristics of granite influenced by sample height-to-width ratios and intermediate principal stress under true-triaxial unloading conditions. Rock Mechanics and Rock Engineering, 51(5), 1321-1345. https://doi.org/10.1007/s00603-018-1414-4
Lin, C. K., Chen, Y. S., & Chuang, H. M. (2016). Improving project risk management by a hybrid MCDM model combining DEMATEL with DANP and VIKOR methods – An example of cloud CRM. In J. Hung, N. Yen, & K. C. Li. (Eds.), Frontier Computing (vol. 375, pp. 1033-1040). Springer, Singapore. https://doi.org/10.1007/978-981-10-0539-8_101
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Ma, D., Cai, X., Zhou, Z., & Li, X. (2018a). Experimental investigation on hydraulic properties of granular sandstone and mudstone mixtures. Geofluids, 9216578. https://doi.org/10.1155/2018/9216578
Ma, D., Duan, H., Liu, J., Li, X., & Zhou, Z. (2019). The role of gangue on the mitigation of mining-induced hazards and environmental pollution: An experimental investigation. Science of the Total Environment, 664, 636-448. https://doi.org/10.1016/j.scitotenv.2019.02.059
Ma, D., Rezania, M., Yu, H. S., & Bai, H. B. (2017). Variations of hydraulic properties of granular sandstones during water inrush: Effect of small particle migration. Engineering Geology, 217, 61-70. https://doi.org/10.1016/j.enggeo.2016.12.006
Mahamid, I. (2011). Risk matrix for factors affecting time delay in road construction projects: owner’s perspective. Engineering, Construction and Architectural Management, 18(6), 609617. https://doi.org/10.1108/09699981111180917
Meade, L., & Sarkis, J. (2002). A conceptual model for selecting and evaluating third-party reverse logistics providers. Supply Chain Management, 7(5), 283-295. https://doi.org/10.1108/13598540210447728
Nývlt, O., Prívara, S., & Ferkl, L. (2011). Probabilistic risk assessment of highway tunnels. Tunnelling and Underground Space Technology, 26(6), 71-82. https://doi.org/10.1016/j.tust.2010.06.010
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Roy, J. (2010). Dealing with uncertainty: selecting a risk analysis tool on the basic project characteristics and phases (Master thesis). Department of Civil, Environmental and Architectural Engineering, University of Colorado, USA.
Roy, J., Chatterjee, K., Bandyopadhyay, A., & Kar, S. (2018). Evaluation and selection of medical tourism sites: A rough analytic hierarchy process based multi‐attributive border approximation area comparison approach. Expert Systems, 35(1), ID 12232. https://doi.org/10.1111/exsy.12232
Saaty, T. L. (1999). Fundamentals of the analytic network process. In Proceedings of the Fifth International Symposium on the Analytic Hierarchy Process. Kobe, Japan.
Saaty, T. L. (2001). Decision making with dependence and feedback: The Analytic network process. Ellsworth Avenue: Pittsburgh Publications.
Saaty, T. L. (2004). Fundamentals of the analytic network process-dependence and feedback in decision-making with a single network. Journal of Systems Science and Systems Engineering, 13(2), 129-157. https://doi.org/10.1007/s11518-006-0158-y
Santos, R., & Jungles, A. (2016). Risk level assessment in construction projects using the schedule performance index. Journal of Construction Engineering, ID 5238416, 1-8. https://doi.org/10.1155/2016/5238416
Seyedhoseini, S. M., Noori, S., & Hatefi, M. A. (2009). An integrated methodology for assessment and selection of the project risk response actions. Risk Analysis, 29(5), 752-763. https://doi.org/10.1111/j.1539-6924.2008.01187.x
Sharma, H. K., Roy, J., Kar, S., & Prentkovskis, O. (2018). Multi criteria evaluation framework for prioritizing Indian railway stations using modified rough AHP-Mabac method. Transport and Telecommunication, 19(2), 113-127. https://doi.org/10.2478/ttj-2018-0010
Shin, D., Shin, Y., & Kim, G. (2016). Comparison of risk assessment for a nuclear power plant construction project based on analytic hierarchy process and fuzzy analytic hierarchy process. Journal of Building Construction & Planning Research, 4(3), 157-171. https://doi.org/10.4236 /jbcpr.2016.43010
Son, N. T. K. (2018). A foundation on semigroups of operators defined on the set of triangular fuzzy numbers and its application to fuzzy fractional evolution equations. Fuzzy Sets and Systems, 347, 1-28. https://doi.org/10.1016/j.fss.2018.02.003
Tang, Y. C., & Beynon, M. J. (2005). Application and development of a fuzzy analytic hierarchy process within a capital investment study. Journal of Economics & Management, 1(2), 207-230.
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