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Equitable optimized airspace sectorization based on constraint programming and OWA aggregation

Abdessamed Mogtit (Aeronautical Sciences Laboratory, Aeronautical and Spatial Studies Institute, BLIDA1 University, Blida, Algeria)
Noureddine Aribi (LITIO Lab., Université Oran1, Oran, Algeria)
Yahia Lebbah (LITIO Lab., Université Oran1, Oran, Algeria)
Mohand Lagha (Aeronautical Sciences Laboratory, Aeronautical and Spatial Studies Institute, BLIDA1 University, Blida, Algeria)

Aircraft Engineering and Aerospace Technology

ISSN: 0002-2667

Article publication date: 15 July 2020

Issue publication date: 21 August 2020

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Abstract

Purpose

Airspace sectorization is an important task, which has a significant impact in the everyday work of air control services. Especially in recent years, because of the constant increase in air traffic, existing airspace sectorization techniques have difficulties to tackle the large air traffic volumes, creating imbalanced sectors and uneven workload distribution among sectors. The purpose of this paper is to propose a new approach to find optimal airspace sectorization balancing the traffic controller workload between sectors, subject to airspace requirements.

Design/methodology/approach

A constraint programming (CP) model called equitable airspace sectorization problem (EQASP) relies on ordered weighted averaging (OWA) multiagent optimization and the parallel portfolio architecture has been developed, which integrates the equity into an existing CP approach (Trandac et al., 2005). The EQASP was evaluated and compared with the method of Trandac et al. (2005), according to the quality of workload balancing between sectors and the resolution performance. The comparison was achieved using real air traffic low-altitude network data sets of French airspace for five flight information regions for 24 h a day and the Algerian airspace for three various periods (off peak hours, peak hours and 24 h).

Findings

It has been demonstrated that the proposed EQASP model, which is based on OWA multicriteria optimization method, significantly improved both the solving performance and the workload equity between sectors, while offering strong theoretical properties of the balancing requirement. Interestingly, when solving hard instances, our parallel sectorization tool can provide, at any time, a workable solution, which satisfies all geometric constraints of sectorization.

Practical implications

This study can be used to design well-balanced air sectors in terms of workload between control units in the strategic phase. To fulfil the airspace users’ constraints, one can refer to this study to assess the capacity of each air sector (especially the overloaded sectors) and then adjust the sector’s shape to respond to the dynamic changes in traffic patterns.

Social implications

This theoretical and practical approach enables the development and support of the definition of the “Air traffic management (ATM) Concept Target” through improvements in human factors specifically (balancing workload across sectors), which contributes to raising the level of capacity, safety and efficiency (SESAR Vision of ATM 2035).

Originality/value

In their approach, the authors proposed an OWA-based multiagent optimization model, ensuring the search for the best equitable solution, without requiring user-defined balancing constraints, which enforce each sector to have a workload between two user-defined bounds (Wmin, Wmax).

Keywords

Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable and constructive review of the manuscript. Thanks must also go to Eurocontrol – PRISME for collaboration and providing datasets for airspace sectorization and making the study possible.

This research was supported by the Directorate General of Scientific Research and Technological Development (DGRSDT) of Algeria.

Citation

Mogtit, A., Aribi, N., Lebbah, Y. and Lagha, M. (2020), "Equitable optimized airspace sectorization based on constraint programming and OWA aggregation", Aircraft Engineering and Aerospace Technology, Vol. 92 No. 8, pp. 1225-1243. https://doi.org/10.1108/AEAT-04-2019-0080

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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