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Aircraft Conflict Resolution: A Benchmark Generator

Author

Listed:
  • Mercedes Pelegrín

    (Laboratoire d’Informatique de l’X, École Polytechnique (LIX), 91128 Palaiseau, France)

  • Martina Cerulli

    (Information Systems, Decision Sciences and Statistics Department, ESSEC Business School of Paris, 95000 Cergy-Pontoise, France)

Abstract

Aircraft conflict resolution is one of the major tasks of computer-aided air traffic management and represents a challenging optimization problem. Many models and methods have been proposed to assist trajectory regulation to avoid conflicts. However, the question of testing the different mathematical optimization approaches against each other is still open. Standard benchmarks include unrealistic scenarios in which all the flights move toward a common point or completely random generated instances. There is a lack of a common set of test instances that allows comparison of the available methods under a variety of heterogeneous and representative scenarios. We present a flight deconfliction benchmark generator that allows the user to choose between (i) different predefined scenario inspired by existing benchmarks in the literature; (ii) pseudo-random traffic meeting certain congestion measurements; (iii) and randomly generated traffic. The proposed setting can account for different levels of difficulty in the deconfliction of the aircraft and allows to explore and compare the real limitations of optimization approaches for aircraft conflict resolution.

Suggested Citation

  • Mercedes Pelegrín & Martina Cerulli, 2023. "Aircraft Conflict Resolution: A Benchmark Generator," INFORMS Journal on Computing, INFORMS, vol. 35(2), pages 274-285, March.
  • Handle: RePEc:inm:orijoc:v:35:y:2023:i:2:p:274-285
    DOI: 10.1287/ijoc.2022.1265
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    References listed on IDEAS

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    1. Martina Cerulli & Claudia D’Ambrosio & Leo Liberti & Mercedes Pelegrín, 2021. "Detecting and solving aircraft conflicts using bilevel programming," Journal of Global Optimization, Springer, vol. 81(2), pages 529-557, October.
    2. Dias, Fernando H.C. & Hijazi, Hassan & Rey, David, 2022. "Disjunctive linear separation conditions and mixed-integer formulations for aircraft conflict resolution," European Journal of Operational Research, Elsevier, vol. 296(2), pages 520-538.
    3. Sonia Cafieri & Nicolas Durand, 2014. "Aircraft deconfliction with speed regulation: new models from mixed-integer optimization," Journal of Global Optimization, Springer, vol. 58(4), pages 613-629, April.
    4. David Rey & Christophe Rapine & Rémy Fondacci & Nour-Eddin El Faouzi, 2016. "Subliminal Speed Control in Air Traffic Management: Optimization and Simulation," Transportation Science, INFORMS, vol. 50(1), pages 240-262, February.
    5. Lehouillier, Thibault & Omer, Jérémy & Soumis, François & Desaulniers, Guy, 2017. "Two decomposition algorithms for solving a minimum weight maximum clique model for the air conflict resolution problem," European Journal of Operational Research, Elsevier, vol. 256(3), pages 696-712.
    Full references (including those not matched with items on IDEAS)

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