A.A. Galyaev, E.A. Ryabushev. Local Dynamic Planning for the defense of a mobile target against an attack of the high-speed hunter with limited vision ... P. 30-43

The problem of protecting a moving target from an attack by a high-speed interceptor using decoy protectors is considered. A minimal self-consistent model of the problem is constructed, based on simple motions and greedy logic governing the interceptor-predator’s movement. Within this model, an exact formulation of the defense planning problem is given, aiming to maximize a tuple quality criterion. The proposed problem statement is shown to be adjacent to a wide class of problems known as the Inverse Dynamic Traveling Salesman Problem. For the formulated problem, a suboptimal planning algorithm is developed to construct acceptable solutions in fast polynomial time. The constructed algorithm is then examined on specific examples of initial data, and a statistical analysis of its performance is conducted.

Keywords: dynamic programming, mathematical optimization, inverse dynamic traveling salesman problem, operations research, mathematical modeling

Received February 20, 2026

Revised April 01, 2026

Accepted May 25, 2026

Andrey Alexeevich Galyaev, Dr. Eng. Sci., Corresponding Member of RAS, Institute of Control Sciences of the Russian Academy of Sciences, Moscow, 117997 Russia, e-mail: galaev@ipu.ru

Efim Alekseevich Ryabushev, Institute of Control Sciences of the Russian Academy of Sciences, Moscow, 117997 Russia, e-mail: lispandhaskell@gmail.com

REFERENCES

1.   Buzikov M.E., Galyaev A.A. Time-optimal interception of a moving target by a dubins car. Autom. Remote Control, 2021, vol. 82, no. 5, pp. 745–758. https://doi.org/10.1134/S0005117921050015

2.   Galyaev A.A., Yakhno V.P., Lysenko P.V., Berlin L.M., Buzikov M.E. Optimization of interception plan for rectilinearly moving targets. Autom. Remote Control, 2023, vol. 84, no. 10, pp. 1026–1038. https://doi.org/10.1134/S000511792310003X

3.   Galyaev A.A., Ryabushev E.A. Searching for a sub-optimal solution of the dynamic traveling salesman problem using the Monte Carlo method. Autom. Remote Control, 2024, vol. 85, no. 2, pp. 162–173. https://doi.org/10.1134/S0005117924020048

4.   Buzikov M.E., Galyaev A.A. Minimum-time lateral interception of a moving target by a Dubins car. Automatica, 2022, vol. 135, art. no. 109968. https://doi.org/10.1016/j.automatica.2021.109968

5.   Buzikov M.E., Mayer A.M. Minimum-time interception of a moving target by a material point in a viscous medium. Automatica, 2024, vol. 167, art. no. 111795. https://doi.org/10.1016/j.automatica.2024.111795

6.   Buzikov M., Galyaev A. The game of two identical cars: an analytical description of the barrier. J. Optim. Theory Appl., 2023, vol. 198, pp. 998–1018. https://doi.org/10.1007/s10957-023-02278-1

7.   Samokhin A., Samokhina M., Grigoriev I., Zapletin M. Base on Phobos–Much safer exploration of Mars without the need for humans on the surface of the planet. Acta Astronautica, 2023, vol. 204, pp. 920–925. https://doi.org/10.1016/j.actaastro.2022.12.028

8.   Samokhina M., Samokhin A. About the 10th edition of the global trajectory optimization competition GTOC — Settlers of the Galaxy. In: Proc. XLIV Academic space conf.: dedicated to the memory of academician S.P.Korolev and other outstanding Russian scientists — Pioneers of space exploration, 2020, Moscow, Russia. 2021, vol. 2318, no. 1, 6 p. https://doi.org/10.1063/5.0035910

9.   Samokhin A.S., Samokhina M.A., Galyaev A.A. About the GTOC XII problem. In: Abstracts 14th Moscow Solar System Symposium (14M-S3), Moscow, IKI RAS, 2023, pp. 284.

10.   Chung Y., Demange M. On inverse traveling salesman problems. 4OR-Q J. Oper. Res., 2012, vol. 10, pp. 193–209. https://doi.org/10.1007/s10288-011-0194-4

11.   Ivanová M., Surynek P., Hirayama K. Area protection in adversarial path-finding scenarios with multiple mobile agents on graphs a theoretical and experimental study of strategies for defense coordination // Proc. 10th Inter. Conf. Agents and Artificial Intelligence (ICAART 2018). Funchal, Madeira, Portugal, 2018. Vol. 2. P. 184–191. https://doi.org/10.5220/0006583601840191

12.   Li X., Zhang Sh. Learning-based TSP-solvers tend to be overly greedy. 2025, 19 p. https://doi.org/10.48550/arXiv.2502.00767

13.   Biediger D.E. Pursuit and evasion of drone swarms and turrets: PhD Thesis, 2022, 110 p.

14.   Blom M., Krumke S.O., de Paepe W.E., Stougie L. The online-TSP against fair adversaries. In: Bongiovanni G., Petreschi R., Gambosi G. (eds.) Algorithms and Complexity (CIAC 2000). Ser. Lecture Notes in Comput. Sci., vol. 1767. Springer, Berlin, Heidelberg, 2000, pp. 137–149. https://doi.org/10.1007/3-540-46521-9_12

15.   Subbotin A.I., Chentsov A.G. Optimizatsiya garantii v zadachakh upravleniya [Guarantee optimization in control problems]. Moscow, Nauka Publ., 1981, 288 p.

16.   Krasovskii N.N., Subbotin A.I. Game-theoretical control problems. NY, Springer, 1988, 517 p. ISBN: 978-1-4612-8318-8 . Original Russian text was published in Krasovskii N. N., Subbotin A. I. Pozitsionnye differentsial’nye igry, Moscow, Nauka Publ., 1974, 456 p.

17.   Joshy A.J., Hwang J. PySLSQP: A transparent Python package for the SLSQP optimization algorithm modernized with utilities for visualization and post-processing. 2024, 9 p. https://doi.org/10.48550/arXiv.2408.13420

Cite this article as: A.A. Galyaev, E.A. Ryabushev. Local Dynamic Planning for the defense of a mobile target against an attack of the high-speed hunter with limited vision. Trudy Instituta Matematiki i Mekhaniki UrO RAN, 2026, vol. 32, no. 3, pp. 30–43.