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Solving the problem of risk synthesis as part of infrastructure facility management

https://doi.org/10.21683/1729-2646-2020-20-4-42-49

Abstract

Aim. Infrastructure facility management involves many decision-making problems that require estimating alternatives in the absence of clear criteria. Sufficiently common are problems that require the consideration of various numbers of factors. Those factors normally belong to different fields of knowledge and require the involvement of subject-area experts. Thus, for instance, the estimation of infrastructure facilities may involve economists, experts in land law, environment, logistics, design engineers and other specialists. The problem is often complicated by the existence of many alternatives. In such cases, it is difficult to organize even the initial expert evaluation in order to reduce the number of options for subsequent consideration. The paper primarily aims to develop a model of evaluation of the criteria that have an effect on the advisability of modernization of an infrastructure facility allowing to take into account factors from various fields of knowledge, as well as to elaborate a method of simplifying the process of evaluation of large numbers of alternative options. Therewith, such estimates can be expressed in various formats: both quantitatively and qualitatively. Such approaches have found application as part of the problem of ranking of airports as part of selection of candidates for inclusion into the Moscow air cluster (MAC). The specificity of this problem consists in the large set of various factors to be taken into account, as well as the great number of options, over 30 airports within 300 kilometers of Moscow. Methods. The risk synthesis model was used that relies on expert data that characterize the criteria that have an effect on the sought risk, as well as the values of damage for each facility by the given criteria. The criteria were estimated using a method based on pairwise comparisons allowing experts to define fuzzy and incomplete estimates of the preferability of the compared options. Damage estimation was done using the method of conversion of qualitative estimates into quantitative ones, as well as scaling of quantitative data into quantitative estimates of damage. Results. Implementing the ideas set forth in this paper allowed defining the contribution of eleven criteria that have an effect on the goals associated with relieving the MAC workload. Based on those criteria, specific risks for airports within 300 kilometers of Moscow were evaluated, and integral risks of modernization of each airport were obtained. The airports were then rated in terms of the integral risk of modernization. Conclusion. The suggested method is universal and can be used for decision-making under uncertainty in those domains where it is required to involve experts of various qualification and level of subject-matter knowledge, as well as accounting for many factors along with a great diversity of options.

About the Authors

N. M. Kuzmina
Moscow State Technical University of Civil Aviation
Russian Federation

Natalia M. Kuzmina, Candidate of Engineering, Associate Professor, Senior Lecturer

Moscow



A. N. Ridley
Moscow Aviation Institute (National Research University)
Russian Federation

Alexandra N. Ridley, post-graduate student

Moscow



References

1. Saaty T. Decision making – the Analytic Hierarchy and Network Processes. Moscow: Radio i sviaz; 1993.

2. Tam C.M., Tong T.K.L., Wong Y.W. Selection of concrete pump using the superiority and inferiority ranking method. Journal of construction engineering and management 2004;130(6):827-834.

3. Marzouk M., Amer O., El-Said M. Feasibility study of industrial projects using Simos’ procedure. Journal of Civil Engineering and Management 2013;19(1):59-68. DOI: 10.3846/13923730.2012.734855.

4. Petrovsky A.B. [Decision theory]. Moscow: Academia; 2009. (in Russ.)

5. Roy B. Multicriteria methodology for decision aiding. Dordrecht: Kluwer Academic Publishers; 1996.

6. Roy B., Bouyssou D. Aide multicritere a la decision: Methodes et cas. Paris: Economica; 1993.

7. Vincke P. Multicriteria decision aid. Chichester: Wiley; 1992.

8. Greco S., Matarazzo B., Slowinski R. Rough sets methodology for sorting problems in presence of multiple attributes and criteria. European Journal of Operational Research 2002;138(2):247-259.

9. Arakelian K.M. [Moscow air cluster development model]. Nauka i transport. Grazhdanskaya aviatsiya 2013;3(7):46-49. Available at: http://www.rostransport.com/science_transport/pdf/7/46-49.pdf. (in Russ.)

10. Ridley A.N. [Method of risk synthesis in system management]. In: Abstracts of the Gagarin Science Conference 2019. Moscow: MAI; 2019. p. 713-714. [accessed 11.05.2020]. Available at: https://gagarin.mai.ru/files/2019/Abstracts_2019.pdf.

11. Karlin L.N., Muzalevskij A.A. Risk researches in RSHU. Life Safety 2011;2:5-19. (in Russ.)

12. Dmitriev V.V. [Defining the integrated indicator of the state of a natural object as a complex system]. Society. Environment. Development 2009;4:146-165. (in Russ.)

13. Potapov A.I., Vorobiov V.N., Karlin L.N. et al. [Monitoring, supervision, quality management of the environment: a scientific and study reference book in 3 parts. Part 3. Assessment and quality management of the environment]. Saint Petersburg: RSHU; 2005. (in Russ.)

14. Shitikov V.G., Rozenberg G.S., Zinchenko T.D. [Quantitative hydroecology: methods, criteria, solutions]. Moscow: Nauka; 2005. (in Russ.)

15. Artobolevsky I.I., Russman I.B., Sergeev V.I. et al. [On some methods of selection of integral criteria of quality in respect to optimal design of machines]. Proceedings of the Academy of Sciences of the USSR 1978;2:3-10. (in Russ.)

16. Kaplinsky A.I., Russman I.B., Umyvakin V.M. [Algorithmization and simulation of ill-defined problems of best system variants selection]. Voronezh: VSU Publishing; 1991. (in Russ.)

17. Arnold V.I. [Catastrophe theory]. Moscow: Nauka; 1990. (in Russ.)

18. Zibrov G.V., Umyvakin V.M., Matviets D.A. [Geoecologic qualimetry of natural/economic territorial systems]. Ecological Systems and Devices 2011;5:3-9. (in Russ.)

19. Bochkov A.V., Zhigirev N.N., Ridley A.N. Method of recovery of priority vector for alternatives under uncertainty or incomplete expert assessment. Dependability 2017;17(3):41-48.

20. Xu Z.S. Goal programming models for obtaining the priority vector of incomplete fuzzy preference relation. International Journal of Approximate Reasoning 2004;36(3):261-270.

21. Borodulina S., Sokolov V., Okuneva A. Logistics of passenger flow forecasting at air transport, with the impact of regional factors. Logistics 2015;4(101):34-39. (in Russ.) Available at: http://www.logistika-prim.ru/sites/default/files/s02_log_0415.pdf.


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Kuzmina N.M., Ridley A.N. Solving the problem of risk synthesis as part of infrastructure facility management. Dependability. 2020;20(4):42-49. https://doi.org/10.21683/1729-2646-2020-20-4-42-49

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ISSN 1729-2646 (Print)
ISSN 2500-3909 (Online)