Methodology for managing the emergency response process based on multi-criteria optimization methods

In modern conditions, due to the unstable economic and political situation around the world, emergencies of various natures are becoming more frequent and large-scale phenomena. This is caused both by natural factors and man-made reasons, as well as by deliberate actions resulting from conflicts and sabotage, which necessitates the improvement of rapid response methods. Consequently, the relevance of developing automated decision support systems for effectively countering contemporary challenges and threats in the field of emergency consequence management is increasing. This paper describes a methodology for the effective management of a set of works and measures for emergency response, based on multi-criteria optimization methods. The following were chosen as optimization criteria: efficiency or the ability to complete assigned tasks in the shortest possible time, availability or the ability to provide resources for all work being carried out in the required volume, and information content or the implementation of measures to ensure up-to-date and objective information about the current situation. Three models for conducting optimization and obtaining a Pareto-optimal solution are considered: the generalized objective function method, the criterion constraints method, and the method of successive concessions. The article provides the mathematical formulation and description of the models and presents an algorithm for selecting a model for different conditions.

1. Sukhanov V.O., Kuzmin A.I., Skorokhodov D.V. Geoinformation system support decision-making on evacuation of the population. Modern Technologies for Civil Defense and Emergency Response. 2019;(1):411–413. (In Russ.).

2. Li T., Sun J., Fei L. Application of Multiple-Criteria Decision-Making Technology in Emergency Decision-Making: Uncertainty, Heterogeneity, Dynamicity, and Interaction. Mathematics. 2025;13(5). https://doi.org/10.3390/math13050731

3. Rodzin S.I., Bozhenyuk A.V., Kravchenko Yu.A., Rodzina O.N. Methods of fuzzy multicriteria group decision-making for evacuation tasks in emergency situations. Izvestiya SFedU. Engineering Sciences. 2023;(2):186–200. (In Russ.). https://doi.org/10.18522/2311-3103-2023-2-186-200

4. Bakir M.E., Kasimoglu F. An integrated multi-criteria decision-making model for long-term planning of UAVs in disaster management. PLoS One. 2026;21(1). https://doi.org/10.1371/journal.pone.0340303

5. Podinovskiy V.V., Nogin V.D. Pareto-optimal solutions of multi-criteria problems. Moscow: Nauka; 1982. 256 p. (In Russ.).

6. Khomenyuk V.V. Elements of the theory of multi-objective optimization. Moscow: Nauka; 1983. 124 p. (In Russ.).

7. Ananev A.V., Ivannikov K.S. Risk-model for communication networks operation stability assessment. In: International Conference "Applied Mathematics, Computational Science and Mechanics: Current Problems" (AMCSM 2020): Journal of Physics: Conference Series: Volume 1902, 07–09 December 2020, Voronezh, Russia. IOP Publishing Ltd; 2021. https://doi.org/10.1088/1742-6596/1902/1/012028

8. Mashunin Yu.K. Methods and models of vector optimization. Moscow: Nauka; 1986. 140 p. (In Russ.).

9. Steuer R.E. Multiple Criteria Optimization: Theory Computation, and Application. Moscow: Radio i svyaz; 1992. 504 p. (In Russ.).

10. Semenov S.S., Voronov E.M., Poltavsky A.V., Kryanev A.V. Decision-making methods in assessing the quality and technical level of complex technical systems. Moscow: URSS, Lenand; 2016. 517 p. (In Russ.).