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A novel group decision making method for airport operational risk management

1. School of Air traffic Management, Civil Aviation University of China, Tianjin 300300, China
2. School of Transportation, Nantong University, Nantong 226019, China
3. CAAC Key laboratory of General Aviation Operation (Civil Aviation Management Institute of China), Beijing 102202, China

Special Issues: Optimization in decision making process

The present research envisages a novel group decision making model to evaluate the operational risk of airports from four aspects of human, equipment, management and environment factors. The proposed model featured an integration of intuitionistic fuzzy set and set pair analysis. Due to the lack of the systematic data and quantitative analysis concerning the uncertainty of these indicators, an intuitionistic fuzzy set was used to characterize them, which converted them into the ternary connection numbers based on set pair analysis. A new distance based on the intuitionistic fuzzy set and set pair analysis was proposed to analyze the consistency degree of any two experts on the same airport operation risk, wherein the degree of contact determined both the uncertainty and certainty of each indicator, so as to obtain the ranking degree of the expert group on the operation risk of all airports. Moreover, the relationship between the value of these indicators and the threshold changes of the airport operation risk ranking was evaluated. This study could be used as an effective tool for transit authorities to rank the operational risk of different airports, by comprehensively considering the viewpoint deviation of different decision makers on the same scheme, and its uncertainty factors. The analysis of the case study comprising four airports in China showed that with an increase in the degree of contact, the operation risk value of the airport in Beijing remained the same that of Tianjin and Qinhuangdao decreased, and for Shijiazhuang gradually increased.
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References

1. F. Netjasov, M. Janic, A review of research on risk and safety modeling in civil aviation, J. Air Transp. Manag., 14 (2008), 213-220.

2. M. Rong, M. Luo, Y. Chen, The research of airport operational risk alerting model, Dig. Hum. Model., 9745 (2016), 586-595.

3. F. Fabio, M. Massimo, T. Riccardo, Electrical safety of aeronautical ground lighting systems, IEEE Trans. Ind. Appl., 51 (2015), 2003-2008.

4. K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets Syst., 75 (1995), 401-402.

5. A. Kaur, A. Kumar, S. S. Appadoo, A note on approaches to interval intuitionistic trapezoidal fuzzy multiple attribute decision making with incomplete weight information, Int. J. Fuzzy Syst., 17 (2019), 484-489.

6. A. Si, S. Das, S. Kar, An approach to rank picture fuzzy nnumbers for decision making problems, Decis. Mak. Appl. Manag. Eng., 2 (2019), 54-64.

7. K. Q. Zhao, Set pair analysis and its primary application, Explor. Nat., 13 (1994), 67-71.

8. Q. Zou, J. Zhou, C. Zhou, Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP, Stoch. Environ. Res. Risk Assess., 27 (2013), 525-546.

9. F. Yan, K. Xu, D. Li, et al., A novel hazard assessment method for biomass gasification stations based on extended set pair analysis, Plos One, 12 (2017), 1-17.

10. Y. S. Pang, J. K. Liu, L. Zhang, Research on government investment group decision-making method for mega construction projects based on intuitionistic fuzzy distance, J. Xi'an Univ. Arch. Tech., 47 (2015), 734-739.

11. C. Q. Tan, Q. Zhang, Aggregation of opinion in group decision making based on intuitionistic fuzzy distances, Math. Prac. Theo., 36 (20062), 119-124.

12. G. Li, G. Kou, Y. Peng, A group decision making model for integrating heterogeneous information, IEEE Trans. Syst., Man Cybern., 6 (2018), 982-992.

13. H. H. Zhang, G. Kou, L. Peng, Soft consensus cost models for group decision making and economic interpretations, Eur. J. Opera. Res., 3 (2019), 964-980.

14. F. Liu, G.Aiwu,V. Lukovac, M. Vukić, A multicriteria model for the selection of the transport service provider: A single valued neutrosophic DEMATEL multicriteria model, Dec. Mak., 1 (2018), 121-130.

15. L. Shi, R. Luo, Research on risk early-warning model in airport flight area based on information entropy attribute reduction and BP neural network, Int. J. Sec. Its Appl., 9 (2015), 313-322.

16. H. B. Jin, Y. Hong, Y. M. Cai, Safety evaluation model of airport operation based on factor analysis, Ind. Safety Environ. Prot., 41 (2015), 62-65.

17. Y. H. Chang, H. H. Yng, Y. J. Hsiao, Human risk factors associated with pilots in runway excursions, Acc. Anal. Prev., 94 (2016), 227-237.

18. F. Hofer, O. E. Wetter, Operational and human factors issues of new airport security technology-two case studies, J. Transp. Sec., 5 (2012), 21-29.

19. X. Li, F. Li, X. Chen, Study on the configuration and capacity of the lateral runway based on the airport green operation, IOP Confer. Series Eart. Environ. Sci., 63 (2017), 12-32.

20. M. Mostafaee, P. Nassiri, M. H. Behzadi, Investigation of noise pollution in ground safety section of mehrabad airport and its relation with employees hearing loss, J. Health Safety Work, 5 (2015), 7-8.

21. X. L. Luo, D. X. Chen, Research on risk evaluation using rnp technology for operation into high elevation airports with critical terrain, 2nd Int. Sympos. Air. Airworth. (ISAA), 17 (2011), 125-140.

22. D. G. Sun, J. Sun, M. Wang, Application of the improved bow-tie analysis technology in civil airport safey, J. Safety Sci. Tech., 4 (2010), 85-90.

23. H. W. Liu, F. Zhang, Y. M. Cai, Risk assessment of the airport operation based on entropy weight, J. Chongqing Univ. Tech., 30 (2016), 177-184.

24. M. J. Rezaee, S. Yousefi, An Intelligent decision-making approach for identifying and analyzing airport risks, J. Air Transp. Manag., 68 (2017), 1-14.

25. D. K. Y. Wong, D. E. Pitfield, R. E. Caves, et al., The development of a more risk-sensitive and flexible airport safety area strategy: Part I, the development of an improved accident frequency model, Safety Sci., 47 (2009), 913-924.    

26. X. Nie, R. Batta, C. G. Drury, et al., Passenger grouping with risk levels in an airport security system, Eur. J. Opera. Res., 194 (2009), 574-584.    

27. M. Hadjimichael, A fuzzy expert system for aviation risk assessment, Expert Syst. Appl., 36 (2009), 6512-6519.

28. X. Qin, F. Luo, On the safety risk assessment of the airport flight area based on the catas-trophe theory and fuzzy set, J. Safety. Environ., 18 (2018), 1730-1736.

29. X. X. Tang, F. Luo, Human risk assessment of the airport runway incursion based on the grey clustering, J. Univ. Elect. Sci. Tech. Cha., 328 (2015), 11-20.

30. S. Chakraborty, N. Creutzfeldt-Banda, 2010 meltdown-airport closure risk communications in London and NYC. Eur. J. Risk Reg., 2 (2011), 108-110.

31. D. Doherty, Operational safety implications on airfield services at a civilian airport, IEEE Semi. Air. Elec. Syst. Mtg. Safety Clg., (2000), 85-94.

© 2020 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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