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Multiobjective optimization for aircraft conflict resolution. A metaheuristic approach

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  • Alonso-Ayuso, Antonio
  • Escudero, Laureano F.
  • Martín-Campo, F. Javier

Abstract

The conflict resolution problem in Air Traffic Management is tackled in this paper by using a mixed integer linear approximation to a Mixed Integer Nonlinear Optimization (MINO) model that we have presented elsewhere. The aim of the problem consists of providing a new aircraft configuration such that every conflict situation is avoided, a conflict being an event in which two or more aircraft violate the minimum safety distance that they must keep in flight. The initial information consists of the aircraft configuration in a certain time instant: position, velocity, heading angle and flight level. The proposed approach allows the aircraft to perform any of the three possible maneuvers: velocity, turn angle and flight level changes. The nonlinear model involves trigonometric functions which make it difficult to solve, in addition to the integer variables related to flight level changes, among other auxiliary variables. A multicriteria scheme based on Goal Programming is also presented. In order to provide a good solution in short computing time, a Sequential Mixed Integer Linear Optimization (SMILO) approach is proposed. A comparison between the results obtained by using the state-of-the-art MINO solver Minotaur and SMILO is performed to assess the solution’s quality. Based on the computational results that we have obtained in a broad testbed we have experimented with, SMILO provides a very close solution to the one provided by Minotaur practically for all the instances. SMILO requires a very small computing time that makes the approach very suitable for helping to solve real-life operational situations.

Suggested Citation

  • Alonso-Ayuso, Antonio & Escudero, Laureano F. & Martín-Campo, F. Javier, 2016. "Multiobjective optimization for aircraft conflict resolution. A metaheuristic approach," European Journal of Operational Research, Elsevier, vol. 248(2), pages 691-702.
    • Handle: RePEc:eee:ejores:v:248:y:2016:i:2:p:691-702
    DOI: 10.1016/j.ejor.2015.07.049
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    References listed on IDEAS

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    1. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    2. Scott Kolodziej & Pedro Castro & Ignacio Grossmann, 2013. "Global optimization of bilinear programs with a multiparametric disaggregation technique," Journal of Global Optimization, Springer, vol. 57(4), pages 1039-1063, December.
    3. A. Alonso-Ayuso & L. Escudero & F. Martín-Campo, 2014. "On modeling the air traffic control coordination in the collision avoidance problem by mixed integer linear optimization," Annals of Operations Research, Springer, vol. 222(1), pages 89-105, November.
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    Cited by:

    1. María Sierra-Paradinas & Antonio Alonso-Ayuso & Francisco Javier Martín-Campo & Francisco Rodríguez-Calo & Enrique Lasso, 2020. "Facilities Delocation in the Retail Sector: A Mixed 0-1 Nonlinear Optimization Model and Its Linear Reformulation," Mathematics, MDPI, vol. 8(11), pages 1-19, November.
    2. Charis Ntakolia & Dimitrios V. Lyridis, 2022. "A n − D ant colony optimization with fuzzy logic for air traffic flow management," Operational Research, Springer, vol. 22(5), pages 5035-5053, November.
    3. Thibault Lehouillier & Moncef Ilies Nasri & François Soumis & Guy Desaulniers & Jérémy Omer, 2017. "Solving the Air Conflict Resolution Problem Under Uncertainty Using an Iterative Biobjective Mixed Integer Programming Approach," Transportation Science, INFORMS, vol. 51(4), pages 1242-1258, November.

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