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A n − D ant colony optimization with fuzzy logic for air traffic flow management

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Abstract

Recent studies show that the number of flights is expected to be increased significantly by 2030, leading to air traffic capacity and congestion issues in the air sectors. This challenging management of the anticipated volume of flights has emerged new derivatives and procedures from the European Union and EUROCONTROL. Aligned with the new vision of future Air Traffic Flow Management (ATFM), such as Trajectory Based Operations, this study proposes a mixed integer nonlinear formulation of ATFM based on 4D trajectories and free flight aspects. The model targets to minimize the total costs derived from airborne and ground holding delays, speed deviations, route alterations and cancellation policies. To solve the proposed nonlinear formulation, a novel n − D ant colony optimization algorithm integrated with fuzzy logic (n − DACOF) is presented. Each flight level is represented as graph and the n − D stands for the n number of permitted flight levels. n − DACOF can solve the ATFM problem by constructing a route moving among n graphs. Due to the multi-objective formulation, fuzzy logic permits the qualitative evaluation of the generated routes by the algorithm. The results showed that n − DACOF outperformed the baseline algorithm ACO, as well as, the CPLEX solver within computing time limits.

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Notes

  1. https://en.about.aegeanair.com/company/fleet/.

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Acknowledgements

This paper is based on the results of the successfully completed three-year research project OPTINET. OPTINET has been co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call “Research-Create-Innovate” (Project Code: Τ1ΕΔΚ-01907).

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Authors and Affiliations

  1. Department of Aeronautical Studies, Sector of Materials Engineering, Machining Technology and Production Management, Dekelia Air Base, Hellenic Air Force Academy, 1919, Acharnes, Athens, GR, Greece

    Charis Ntakolia

  2. Laboratory for Maritime Transport, National Technical University of Athens, 157 72, Zografou, Athens, Greece

    Charis Ntakolia & Dimitrios V. Lyridis

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  1. Charis Ntakolia
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  2. Dimitrios V. Lyridis
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Correspondence to Charis Ntakolia.

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Ntakolia, C., Lyridis, D.V. A n − D ant colony optimization with fuzzy logic for air traffic flow management. Oper Res Int J 22, 5035–5053 (2022). https://doi.org/10.1007/s12351-021-00686-7

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