Application of artificial locust swarm routing algorithm for VFR flights planning

  • 1 Lviv Polytechnic National University, Lviv, Ukraine
  • 2 Lviv Polytechnic National University, Lviv, Ukraine; RocketRoute Ltd, Farnborough, Hampshire, UK


Along recent years an approach of Artificial Locust Swarm Routing (ALSR) algorithm was developed for flights planning in Europe and for rules provided in EuroControl area of responsibility. Most researches were strictly related to IFR type of flights. However, there is a big area of interest in private aviation for short local flights under the top of VFR flight levels (FL195 and below). These flights have much specificity for planning and ALSR algorithm is found capable of solving these problems also, using this same idea of the algorithm like it was developed for IFR flights. One may see that the algorithm shows rather good results for such difficult area like Swiss Alps valleys and canyons.



  1. Thomas R. Kurfess, Robotics and Automation Handbook. – CRC Press, 2018. – 608 p.
  2. K. Schwab, The Fourth Industrial Revolution. – NY: Crown Publishing Group, 2016 (2017). – 192 p.
  3. An approach of FRA and its use for UFV supported manufacturing / V. Alieksieiev, B. Liubinsky, V. Hladun // ―Machines. Technologies. Materials.‖ – Scientific-Technical Union of Mechanical Engineering ―Industry 4.0‖ (Sofia, BULGARIA), 2019 – Volume 13, Issue 10. – P.437–438. —
  4. Implementation of UAV for environment monitoring of a Smart City with an airspace regulation by AIXM-format data streaming / Vladyslav Alieksieiev, Bohdan Markovych // ―Industry 4.0‖ – Scientific-Technical Union of Mechanical Engineering ―Industry 4.0‖ (Sofia, BULGARIA), 2020 – Volume 5, Issue 2. – P.90–93. —
  5. E.W. Dijkstra, ―A note on two problems in connexion with graphs‖, Numerische Mathematik, Vo l. 1, Iss. 1, pp. 269–271 (1959)
  6. P.E. Hart, N.J. Nilsson, B. Raphael, ―A Formal Bas is for the Heuristic Determination of Minimum Cost Paths‖, IEEE Transactions on Systems Science and Cybernetics SSC4 (2), pp. 100–107 (1968)
  7. H. Berliner, ―The B* tree search algorithm. A best-first proof procedure‖, Artific ial Intelligence, Vol. 12, Iss. 1, pp. 23–40 (1979)
  8. A. Stentz, ―Optimal and Effic ient Path Planning for Partially- Known Environments‖, IEEE International Conference on Robotics and Automation, vol. 4, pp. 3310–3317 (1994)
  9. R.J. Szczerba, D.Z. Chen, J.J. Uhran Jr. ―Planning shortest paths among 2D and 3D weighted regions using framed-subspaces‖, The International Journal of Robotics Research, Vol. 17, No. 5, 1998, pp. 531–546.
  10. J.O. Royset, W.M. Carlyle, R.K. Wood, ―Routing military aircraft with a constrained shortest-path algorithm‖, Military Operations Research, Vol. 14, No. 3, 2009, pp. 31–52.
  11. Shijin Wang, Xi Cao, Haiyun Li, Qingyun Li, Xu Hang, Yanjun Wang, ―Air route network optimization in fragmented airspace based on cellular automata‖, Chinese Journal of Aeronautics, No. 30 (3), 2017, pp. 1184–1195.
  12. C. K. Jensen, M. Chiarandini, K. S. Larsen, ―Flight planning in free route airspaces‖, 17th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2017), 2017 – 14 p.
  13. M. Dorigo, ―Optimization, Learning and Natural Algorithms‖, PhD thesis, Politecnico di Milano, Italy, 1992.
  14. M. Dorigo, G.A. Di Caro, L.M. Gambardella, ―Ant Algorithms for Discrete Optimization‖, Artific ial Life, vol. 5, pp. 137–172 (1999)
  15. D. Karaboga, B. Basturk, ―A Powerful and Effic ient Algorithm for Numerical Function Optimization: Artificial Bee Colony (ABC) Algorithm‖, Journal of Global Optimization, Vol. 39, No. 3, pp. 459–471 (2007)
  16. A novel meta-heuristic algorithm for numerical function optimization: Blind, naked mole-rats (BNMR) algorithm / Mohammad Taherdangkoo, Mohammad Hossein Shirzadi, and Mohammad Hadi Bagheri. // Scientific Research and Essays – Vol. 7 (41), Oct. 2012 – P. 3566-3583 – Retrieved from:
  17. Grasshopper Optimisation Algorithm: Theory and application / Saremi S., Mirjalil S., Lewis A. // Advances in Engineering Software – Vol. 105, Mar. 2017 – P.30-47
  18. Air space routing and flights planning: a problem statement and discussion of approaches to solution / V. Alieksieiev // ―Mathematical Modeling‖ – Scientific-Technical Union of Mechanical Engineering ―Industry 4.0‖ (Sofia, BULGARIA), 2018 – Volume 2, Issue 4 – P.139–142. —
  19. V. Alieksieiev, ―Artificial Locust Swarm Routing Algorithm: An Approach to Consider both Routing via FRA and Applying RAD‖, 2019 International Conference on Information and Digital Technologies (IDT), 2019, pp.1-10. —
  20. V. Alieksieiev, A. Berko, ―Artificial Locust Swarm Routing Algorithm: Decision Making in Path Search Problem‖, 2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), 2019, pp.1-6. —
  21. IFPS User Manual – EUROCONTROL, 2019 –
  22. Aeronautical Information Exchange Model –
  23. Free route airspace (FRA) – Eurocontrol,
  24. The approach to cut relevant airspace area for flights planning and automated routing / V. Alieksieiev, I. Alieksieiev // ―Industry 4.0‖ – Scientific-Technical Union of Mechanical Engineering ―Industry 4.0‖ (Sofia, BULGARIA), 2019 – Volume 4, Issue 5. – P.220–222. —
  25. Flight Planning Centre RocketRoute –

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