Investment process optimization of air transport subsidies

One of the significant areas of investment in civil aviation is air transportation subsidies. The article considers the possibility of optimizing management decisions on the distribution of investment volumes among airlines participating in the air transportation route selection program that ensures growth of efficiency indicators with a limited investment resource. To formulate the optimization problem, continuous optimized variables that determine investment volumes and alternative variables corresponding to the choice of a specific transportation route are introduced. The initial data provided by the airlines are used to assess the fulfillment of extreme and boundary requirements for the subsidizing process. Each indicator, on the basis of which the specified requirements are formed, is calculated according to the parameters recorded in the initial data, depending on the values of the variables. In this case, it becomes necessary to split the condition of a limited integrated resource into two particular boundary conditions. As a result, we have a multi-criteria optimization problem with constraints, defined on sets of continuous and alternative optimized variables. To solve it, it is proposed to use a combination of an adaptive algorithm of directed randomized search and a particle swarm algorithm. We conduct a computational experiment using an optimization approach, which is compared with actual data on air transport subsidies. The optimized variant of investment distribution and route selection is characterized by values of performance indicators that are better than those actually achieved.

1. Borzova A.S., Ivanov D.V. Optimization Modeling of the Investment Process for the Development of the Civil Aviation Sectoral Organizational System. Modeling, Optimization and Information Technology. 2021;9(1). (In Russ.). https://doi.org/10.26102/2310-6018/2021.32.1.030

2. Kalmikova A. Conditions, Factors of Formation and Development of Modern Market of Investments. Transport Business of Russia. 2012;(5):23–24. (In Russ.).

3. Gorkovenko M.L., Trofimov S.V. Peculiarities of Airport Activities in Conditions of Competition Between Aviation Enterprises Securing Air Transportations. Konkurentnoe pravo. 2020;(1):40–44. (In Russ.).

4. Anisimov Yu.P., Kuksova I.V., Gubertov E.A., Zhilnikov A.Yu., Igolkin I.S. Optimization of Investment Resource Flows for the Development of Innovative Activities at the Enterprise. Proceedings of the Voronezh State University of Engineering Technologies. 2022;84(2):400–406. (In Russ.). http://doi.org/10.20914/2310-1202-2022-2-400-406

5. Bazaluk O., Zhykharieva V., Vlasenko O., Nitsenko V., Streimikiene D., Balezentis T. Optimization of the Equity in Formation of Investment Portfolio of a Shipping Company. Mathematics. 2022;10(3). http://doi.org/10.3390/math10030363

6. Mezhov I.S., Kletskova E.V. Modelling of Regional Economy Growth Strategy. Management Sciences. 2017;7(4):26–35. (In Russ.).

7. Karpenko A.P. Sovremennye tekhniki optimizatsii proektnykh reshenii. In: Intellektual'nye informatsionnye sistemy: trudy Mezhdunarodnoi nauchno-prakticheskoi konferentsii, posvyashchennoi 40-letiyu kafedry SAPRIS, 14–15 February 2024, Voronezh, Russia. Voronezh: Voronezh State Technical University; 2024. P. 9–12. (In Russ.).

8. Ivanov D.V., Lvovich Ya.E. Algorithmization of Management Decision-Making as Part of the Industry Development Program with Random Variations of the Investment Resource. Modeling, Optimization and Information Technology. 2023;11(3). (In Russ.). https://doi.org/10.26102/2310-6018/2023.42.3.006

9. Kondrateva O.V. Intellectual Decision-Making Support Algorithm on the Securities Portfolio Formation Based on the Swarm Intelligence. Modeling, Optimization and Information Technology. 2021;9(2). (In Russ.). http://doi.org/10.26102/2310-6018/2021.33.2.029

10. Karpenko A.P. Methods for Increasing the Efficiency of Swarm Algorithms for Global Optimization. In: BIONIKA-2023: materialy III Mezhdunarodnoi nauchno-prakticheskoi konferentsii, 01–03 November 2023, Moscow, Russia. Moscow: Izd-vo MGTU im. N.E. Baumana; 2024. P. 40–47. (In Russ.).