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Airspace Sector Design: An Optimization Approach

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

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Airspace Sector Design: An Optimization Approach. / Lui, Go Nam; Lulli, Guglielmo; Lema-Esposto, M. Florencia et al.
2024. Paper presented at SESAR Innovation Days 2024, Roma, Italy.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Harvard

Lui, GN, Lulli, G, Lema-Esposto, MF & Llorente Martinez, R 2024, 'Airspace Sector Design: An Optimization Approach', Paper presented at SESAR Innovation Days 2024, Roma, Italy, 12/11/24 - 15/11/24.

APA

Lui, G. N., Lulli, G., Lema-Esposto, M. F., & Llorente Martinez, R. (2024). Airspace Sector Design: An Optimization Approach. Paper presented at SESAR Innovation Days 2024, Roma, Italy.

Vancouver

Lui GN, Lulli G, Lema-Esposto MF, Llorente Martinez R. Airspace Sector Design: An Optimization Approach. 2024. Paper presented at SESAR Innovation Days 2024, Roma, Italy.

Author

Lui, Go Nam ; Lulli, Guglielmo ; Lema-Esposto, M. Florencia et al. / Airspace Sector Design: An Optimization Approach. Paper presented at SESAR Innovation Days 2024, Roma, Italy.

Bibtex

@conference{e4d321e093f84d9aa932dbbb89a89350,
title = "Airspace Sector Design: An Optimization Approach",
abstract = "This paper presents a Mixed Integer Programming model for optimal airspace sector design based on basic volume aggregation, focusing on workload balance and air traffic flow convexity. To overcome potential computational limitations, we develop a simple two-stage heuristic approach. The heuristic approach are evaluated using real-world traffic data from the Madrid Area Control Center, with the MIP as a benchmark. Our key contributions include: (1) the first rigorous mathematical formulation for this problem, (2) a fast heuristic achieving near-optimal solutions in under one second, and (3) a comprehensive assessment across various traffic scenarios. Results show that our MIP model generates operationally relevant sector designs, and the heuristic could provide good-quality solutions with exceptional efficiency. This research advances airspace management techniques, offering both theoretical insights and practical tools for optimizing air traffic control.",
keywords = "Airspace sector design, ; mixed-integer programming (MIP), heuristic approach",
author = "Lui, {Go Nam} and Guglielmo Lulli and Lema-Esposto, {M. Florencia} and {Llorente Martinez}, Rebeca",
year = "2024",
month = nov,
day = "13",
language = "English",
note = "SESAR Innovation Days 2024 ; Conference date: 12-11-2024 Through 15-11-2024",
url = "https://www.sesarju.eu/SIDS2024",

}

RIS

TY - CONF

T1 - Airspace Sector Design: An Optimization Approach

AU - Lui, Go Nam

AU - Lulli, Guglielmo

AU - Lema-Esposto, M. Florencia

AU - Llorente Martinez, Rebeca

PY - 2024/11/13

Y1 - 2024/11/13

N2 - This paper presents a Mixed Integer Programming model for optimal airspace sector design based on basic volume aggregation, focusing on workload balance and air traffic flow convexity. To overcome potential computational limitations, we develop a simple two-stage heuristic approach. The heuristic approach are evaluated using real-world traffic data from the Madrid Area Control Center, with the MIP as a benchmark. Our key contributions include: (1) the first rigorous mathematical formulation for this problem, (2) a fast heuristic achieving near-optimal solutions in under one second, and (3) a comprehensive assessment across various traffic scenarios. Results show that our MIP model generates operationally relevant sector designs, and the heuristic could provide good-quality solutions with exceptional efficiency. This research advances airspace management techniques, offering both theoretical insights and practical tools for optimizing air traffic control.

AB - This paper presents a Mixed Integer Programming model for optimal airspace sector design based on basic volume aggregation, focusing on workload balance and air traffic flow convexity. To overcome potential computational limitations, we develop a simple two-stage heuristic approach. The heuristic approach are evaluated using real-world traffic data from the Madrid Area Control Center, with the MIP as a benchmark. Our key contributions include: (1) the first rigorous mathematical formulation for this problem, (2) a fast heuristic achieving near-optimal solutions in under one second, and (3) a comprehensive assessment across various traffic scenarios. Results show that our MIP model generates operationally relevant sector designs, and the heuristic could provide good-quality solutions with exceptional efficiency. This research advances airspace management techniques, offering both theoretical insights and practical tools for optimizing air traffic control.

KW - Airspace sector design

KW - ; mixed-integer programming (MIP)

KW - heuristic approach

UR - https://www.sesarju.eu/sites/default/files/documents/sid/2024/papers/SIDs_2024_paper_069%20final.pdf

M3 - Conference paper

T2 - SESAR Innovation Days 2024

Y2 - 12 November 2024 through 15 November 2024

ER -