Russian Federation
Saint-Petersburg University of State Fire Service of Emercom of Russia
Russian Federation
Decision-making problems in emergency response are usually fraught with risk and uncertainty due to limited data and a relatively large number of possible incident scenarios. These factors influence decision makers in the context of selecting a response or set of activities in emergency response. To solve this problem, we propose a methodology based on failure tree analysis, which is used to describe the logical relationships between the conditions and factors that lead to the occurrence and development of an emergency. The use of this methodology allows to consider different alternative response actions taking into account different scenarios of emergency development, to rank possible alternative actions and to choose the most effective one. A promising direction for future research is to realise the possibility of using the proposed methodology when the probabilities of the main events are in an uncertain form or are characterised by fuzzy data, which will require the use of linguistic variables in the assessment and the apparatus of fuzzy logic.
emergency, emergency decision making, fault tree analysis, fault tree, response
1. Zavorotny A.G., Kostrubitsky A.A. Algorithmization and software implementation of the management model for the population protection system in man-made emergencies // Problems of security and emergencies. – 2021. – No. 4. – P. 112-124. – DOIhttps://doi.org/10.36535/0869-4179-2021-04-10. – EDN RMULXX.
2. Kalach A.V., Nicheporchuk V.V., Kalach E.V., Kubasov I.A. Design of support systems for the management of natural and man-made safety of territories using ontologies // Bulletin of the Voronezh State University. Series: Systems Analysis and Information Technology. – 2021. – No. 3. – P. 95-105. – DOIhttps://doi.org/10.17308/sait.2021.3/3739. – EDN LUZTCZ.
3. Lyashenko E.N., Sherstyuk V.G. Development of a model for coordinating forces and means in a hierarchical system of civil protection of the population // Technological audit and production reserves. – 2015. – Vol. 4, No. 2(24). – P. 4-10. – DOIhttps://doi.org/10.15587/2312-8372.2015.47180. – EDN UDXIIR.
4. Matveev A.V., Maksimov A.V., Vodnev S.A. Model for a comprehensive assessment of the process of technical support of emergency rescue equipment of the EMERCOM of Russia // Problems of risk management in the technosphere. – 2018. – No. 2(46). – P. 73-80. – EDN YLLCZN.
5. Matyushin A.V., Poroshin A.A., Bobrinev E.V., Kondashov A.A., Matyushin Yu.A., Terekhov A.V. Modern geoinformation technologies in designing fire protection garrisons // Fire safety. – 2012. – No. 3. – P. 107-119. – EDN PHSLGR.
6. Perevalov A.S., Sugak V.P. Game methods for selecting the optimal plan for conducting search and rescue operations // Scientific and analytical journal "Bulletin of the St. Petersburg University of the State Fire Service of the Ministry of Emergency Situations of Russia". – 2013. – No. 3. – P. 8-12. – EDN RSMMEL.
7. Topolsky N.G., Tarakanov D.V. Algorithm for ranking management tasks in the decision-making support system for emergency response // Technologies of technosphere safety. – 2014. – No. 2 (54). – P. 27. – EDN TGSMCR.
8. Shofeev T.G. Model of decision-making in responding to emergencies under uncertainty // Scientific and analytical journal "Bulletin of the St. Petersburg University of the State Fire Service of the Ministry of Emergency Situations of Russia". – 2023. – No. 1. – P. 190-203. - EDN HCRSUA.
9. Maksimov A.V. Methods of decision support in operational management of emergency situations: a research review // National security and strategic planning. – 2023. – No. 2 (42). – P. 91-102. – DOIhttps://doi.org/10.37468/2307-1400-2023-2-91-102. – EDN CJCPWN.
10. Viktorova V.S., Stepanyants A.S. Dynamic Fault Trees // Reliability. – 2011. – No. 3(38). – P. 20-32. – EDN OSKKBL.
11. Butyrsky E.Yu., Matveev A.V. Mathematical Modeling of Systems and Processes. – St. Petersburg: Information Publishing Educational and Scientific Center "Strategy of the Future", 2022. – 733 p. – ISBN 978-5-4268-0064-9. – DOIhttps://doi.org/10.37468/book_011222. – EDN CCRIRT.
12. Dnekeshev A.A. Dynamic fault tree for the analysis of emergency situations at oil refineries // Science Bulletin. – 2022. – Vol. 3, No. 8(53). – P. 19-30. - EDN DXDFRN.
13. Kolosok I.N., Korkina E.S., Tikhonov A.V. Reliability analysis of a software and computing complex for state assessment based on fault tree technology // Electricity. – 2018. – No. 6. – P. 24-34. – DOIhttps://doi.org/10.24160/0013-5380-2018-6-24-34. - EDN XOTSLR.
14. Muradov A.V., Volokhina A.T., Glebova E.V., Ivanova M.V. Accident Rate of Main Gas Pipelines Taking into Account the Human Factor // Life Safety. – 2009. – No. 12 (108). – P. 37-40. – EDN KXYVJH.
15. Nowak M. Aspiration level approach in stochastic MCDM problems // European Journal of Operational Research. – 2007. – Vol. 177. – No. 3. – P. 1626-1640. DOI: https://doi.org/10.1016/j.ejor.2005.10.003
16. Sologubova L.A., Trunkina O.V., Baibekova F.N., Kulakov A.A. Decision Making Using the Analytic Hierarchy Process // Innovations in Science. – 2018. –- No. 4 (80). – P. 11-14. – EDN WBWTQT.
17. Knyshov A.V. Application of group methods in making unprogrammed management decisions // Bulletin of the Russian Customs Academy. – 2018. – No. 4. – P. 95-102. – EDN VNXNDG.
