Risk Evaluation of Airport Safety during Non-stop Construction Using Fuzzy Analytical Hierarchy Process and Bayesian Belief Network

Document Type : Original Article


1 Department of Road Engineering, School of Transportation, Southeast University, Nanjing, China

2 States Key Laboratory of Air Traffic Management System and Technology, Nanjing, China

3 Department of Road Engineering, School of Transportation, Southeast University, Nanjing,China

4 Department of Road Engineering, School of Transportation,Southeast University, Nanjing, China


During the non-stop construction, risk analysis is essential to ensure airport safety. This study aims to perform risk evaluation of airport safety during the non-stop construction using both Fuzzy Analytical Hierarchy Process (F-AHP) and Bayesian Belief Network (BBN). Risk assessment of airport during non-stop construction involves four risk factors of personnel, equipment, environment, and management. F-AHP is utilized to rank impact of risk factors while BBN is implemented to assess probability of risk occurrence. The combination of F-AHP and BBN is implemented to identify the most significant risk. The results have revealed that environmental factor imposes the most significant influence on risk of airport safety during non-stop construction while equipment factor has the lowest impact on airport safety. The outcomes of this study allow decision makers to manage potential risk and improve airport safety during the non-stop construction. 


[1]- Dan, P., Fan, L., and Qin, X., 2017, Airport safety 3d risk measurement model under the circumstance of non-stop flight construction, Agro Food Industry Hi-Tech., 28, 2094-2100.
[2]- Qiao, Y., Ding, W., Xingbang, L., U., et al., 2019, Key points in managing and constructing under crossing projects in airfield area, Earth Science Frontiers, 230-241.
[3]- Mohri, S. S., Karimi, H., Kordani, A. A., et al., 2018, Airline hub-and-spoke network design based on airport capacity envelope curve: A practical view, Computers and Industrial Engineering, 125, 375-393.
[4]- Enny, M. M., Purba, H. H., 2012, Construction project risk analysis based on fuzzy analytical hierarchy process (F-AHP): a Literature Review, Advance Researches in Civil Engineering, 3(3), 1-20.
[5]- Yuen, K. K., 2014, Fuzzy cognitive network process: comparisons with fuzzy analytic hierarchy process in new product development strategy, IEEE Transactions on Fuzzy Systems, 22(3), 597-610.
[6]-Nieto-Morote, A., and Ruz-Vila, F., 2011, A fuzzy approach to construction project risk assessment, International Journal of Project Management, 29(2), 220-231.
[7]- Olabanji, O. M., and Mpofu, K., 2020, Appraisal of conceptual designs: coalescing fuzzy analytic hierarchy process (F-AHP) and fuzzy grey relational analysis (F-GRA), Results in Engineering.
[8]- Pereira, J. C., Fragoso, M. D., and Todorov, M. G., 2016, Risk assessment using bayesian belief networks and analytic hierarchy process applicable to jet engine high pressure turbine assembly, IFAC-Papers on Line,49-12, 133-138.
[9]- Hanea, A. M., Kurowicka, D., and Cooke, R. M., 2010, Hybrid method for quantifying and analyzing bayesian belief nets, Quality and Reliability Engineering International, 22(6), 709-729.
[10]- Mc Donald, K. S.,  Ryder, D. S., and Tighe, M., 2015, Developing best-practice bayesian belief networks in ecological risk assessments for freshwater and estuarine ecosystems: A quantitative review, Journal of Environmental Management, 154, 190-200.
[11]-William, I. I., Millie, D. F., Weckman, G. R., et al., 2011, Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network, Environmental Modelling and Software, 26(10), 1199-1210.
[12]-Bae, J. H., and Park, J. W., 2021, Research into individual factors affecting safety within airport subsidiaries, Sustainability, 13(9), 5219-5238
[13]- Cummings, C. L., Rosenthal, S., and Wei, Y. K., 2021, Secondary risk theory: validation of a novel model of protection motivation, Risk Analysis, 41(1), 204-220.
[14]- Zuo, F., and Zhang, K., 2017, Selection of risk response actions with consideration of secondary risks, International Journal of Project Management, 36(2), 241-254.
[15]- Zhang, Q., and Wang, X. P., 2016, The comparison of some fuzzy operators used in fuzzy comprehensive evaluation models, Fuzzy Systems and Mathematics, 261-263.
[16]- Zhu, H. Z., and Hu, J. B., 2011, Research on model of comprehensive fuzzy assessment of projects post evaluation, Advanced Materials Research, 566-570.