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Geographical information system for air traffic optimization using genetic algorithm

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Abstract

The primary concern of an air traffic controller is to ensure the safety and fluidity of ever-increasing air traffic. This requires effective training through practical work supervised by instructors. Based on certain rules called separation rules, the trainee must find a solution to a traffic configuration defined by flight plans (FPL) initially containing a number of conflicts. This solution will then be compared to the one proposed by the instructor. The purpose of this article is to replace the instructor with a Geographical Information System (GIS) solution combined with a genetic algorithm which, from a set of FPLs, will find the best solution to ensure on the one hand the safety of the aircraft but also minimizing the distance and the changes to be made. The application will use the GAMA platform, very suitable for this and a set of tests composed of actual exercises will be performed to validate the work.

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Authors and Affiliations

  1. LTIR Laboratory, Faculty of Electronics and Computational Science, USTHB University, Algiers, Algeria

    Rafik Amara & Mostefa Belhadj Aissa

  2. Department of Computer Science, Ecole Normale Supérieure de Kouba, Algiers, Algeria

    Rafik Amara, Rebiha Kemcha, Maamar Bougherara & Nadjib Louam

  3. LIMOSE Laboratory, Boumerdes University, Boumerdes, Algeria

    Rebiha Kemcha

  4. LIMPAF Laboratory, Bouira University, Bouira, Algeria

    Maamar Bougherara

Authors
  1. Rafik Amara
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  2. Mostefa Belhadj Aissa
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  3. Rebiha Kemcha
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  4. Maamar Bougherara
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Correspondence to Rafik Amara.

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Amara, R., Belhadj Aissa, M., Kemcha, R. et al. Geographical information system for air traffic optimization using genetic algorithm. Geoinformatica 27, 593–617 (2023). https://doi.org/10.1007/s10707-022-00477-y

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  • DOI: https://doi.org/10.1007/s10707-022-00477-y

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