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A robust optimization approach for designing multi-period airport hub network with uncertain capacity

Authors:
Mohammadmahdi Hajiha at Southern Methodist University
Mohammadmahdi Hajiha
Michel Fathi at University of North Texas
Michel Fathi
Marzieh Khakifirooz at Tecnológico de Monterrey
Marzieh Khakifirooz
Panos M. Pardalos at University of Florida
Panos M. Pardalos
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Abstract and Figures

Airports are increasing their capacity to accelerate and facilitate travel and cargo delivery. At the same time, they aim to decrease expenses on delays caused by capacity overflow, encouraging policymakers to plan to enhance the capacity of crowded airports for the long term and set their transportation policies accordingly. This study develops a mathematical model for designing a network of airports with hub location problems (HLPs) with uncertain practical capacity in addition to their deterministic nominal capacity, using mixed integer programming (MIP). Our methodology proposes a robust optimization framework for uncertain capacity in hub airport facilities. Also, we utilize a practical approach for calculating the transit flow in hub airports by decomposing the flow into incoming, transiting, and outgoing statuses. We use a tailored Benders decomposition algorithm (BDA) to facilitate the solution effort. Numerical results using data envelopment analysis (DEA) show a notable increase in the efficiency of the hub airports with the proposed method. Finally, airport managers can plan to improve the need for air transport infrastructure over a long period.
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Annals of Operations Research
https://doi.org/10.1007/s10479-024-06322-9
ORIGINAL RESEARCH
A robust optimization approach for designing multi-period
airport hub network with uncertain capacity
Mohammadmahdi Hajiha1·Michel Fathi2·Marzieh Khakifirooz3·
Panos M. Pardalos4
Received: 27 January 2024 / Accepted: 19 September 2024
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024
Abstract
Airports are increasing their capacity to accelerate and facilitate travel and cargo delivery.
At the same time, they aim to decrease expenses on delays caused by capacity overflow,
encouraging policymakers to plan to enhance the capacity of crowded airports for the long
term and set their transportation policies accordingly. This study develops a mathematical
model for designing a network of airports with hub location problems (HLPs) with uncertain
practical capacity in addition to their deterministic nominal capacity, using mixed integer
programming (MIP). Our methodology proposes a robust optimization framework for uncer-
tain capacity in hub airport facilities. Also, we utilize a practical approach for calculating the
transit flow in hub airports by decomposing the flow into incoming, transiting, and outgoing
statuses. We use a tailored Benders decomposition algorithm (BDA) to facilitate the solution
effort. Numerical results using data envelopment analysis (DEA) show a notable increase in
the efficiency of the hub airports with the proposed method. Finally, airport managers can
plan to improve the need for air transport infrastructure over a long period.
Keywords Airports network design ·Capacitated hub location problem ·Robust
optimization ·Mixed integer programming ·Benders decomposition algorithm ·Data
envelopment analysis
BMarzieh Khakifirooz
mkhakifirooz@tec.mx
Mohammadmahdi Hajiha
mhajiha@uark.edu
Michel Fathi
mfathi@unt.edu
Panos M. Pardalos
pardalos@ufl.edu
1Department of Industrial Engineering, University of Arkansas, Fayetteville, AR, USA
2Department of Information Technology & Decision Sciences, G. Brint Ryan College of Business,
University of North Texas, Denton, TX, USA
3Department of Industrial Engineering, Tecnologico de Monterrey, Monterrey, NL, Mexico
4Department of Industrial and Systems Engineering, Center for Applied Optimization, University of
Florida, Gainesville, FL, USA
123
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