TY - JOUR
T1 - Post disaster adaptation management in airport: A coordination of runway and hangar resources for relief cargo transports
AU - Qin, Yichen
AU - Ng, Kam K.H.
AU - Hu, Hongtao
AU - Chan, Felix T.S.
AU - Xiao, Shichang
N1 - Funding Information:
The research is supported by the National Natural Science Foundation of China (Grant No. 72101144 , 71971143 and 71771143 ), the Research Grants Council of the Hong kong Special Administrative Region , China ( PolyU 25218321 ) and the Research Committee and the Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University (BE3V); and the Soft Science Key Project of Shanghai Science and Technology Innovation Action Plan (Grant No. 20692193300 ).
Funding Information:
The research is supported by the National Natural Science Foundation of China (Grant No. 72101144, 71971143 and 71771143), the Research Grants Council of the Hong kong Special Administrative Region, China (PolyU 25218321) and the Research Committee and the Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University (BE3V); and the Soft Science Key Project of Shanghai Science and Technology Innovation Action Plan (Grant No. 20692193300).
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/10
Y1 - 2021/10
N2 - Air traffic congestions for processing relief cargos under post-disaster relief scenarios are common, due to high transport demands within a short time. To enhance the resilience of relief operations at airport, an optimization problem of relief air cargo transportations involving aircraft sequencing and loading/unloading within a designated hangar is studied in this paper. The objective is minimizing the tardiness in fulfilling inbound and outbound relief cargos. A mixed-integer linear programming model is formulated, which incorporates aircraft sequencing and hangar parking planning. To resolve the practical problem efficiently, we propose a two-stage optimization approach, which reduces complexity in solving the original model by coordinating the decisions of aircraft landing and take-off schedule and cargo hangar parking arrangement through iterations. The efficiency of the proposed method is examined through the computational results. High-quality solutions can be obtained by the two-stage optimization method within a reasonable time for practical implementation, which enhances the responsiveness and resource utilization of airport operations management under disaster relief situations.
AB - Air traffic congestions for processing relief cargos under post-disaster relief scenarios are common, due to high transport demands within a short time. To enhance the resilience of relief operations at airport, an optimization problem of relief air cargo transportations involving aircraft sequencing and loading/unloading within a designated hangar is studied in this paper. The objective is minimizing the tardiness in fulfilling inbound and outbound relief cargos. A mixed-integer linear programming model is formulated, which incorporates aircraft sequencing and hangar parking planning. To resolve the practical problem efficiently, we propose a two-stage optimization approach, which reduces complexity in solving the original model by coordinating the decisions of aircraft landing and take-off schedule and cargo hangar parking arrangement through iterations. The efficiency of the proposed method is examined through the computational results. High-quality solutions can be obtained by the two-stage optimization method within a reasonable time for practical implementation, which enhances the responsiveness and resource utilization of airport operations management under disaster relief situations.
KW - Adaptive decision-making
KW - Aircraft sequencing and scheduling problem
KW - Airport management
KW - Hangar parking arrangement
KW - Post-disaster relief
UR - http://www.scopus.com/inward/record.url?scp=85113970939&partnerID=8YFLogxK
U2 - 10.1016/j.aei.2021.101403
DO - 10.1016/j.aei.2021.101403
M3 - Journal article
AN - SCOPUS:85113970939
SN - 1474-0346
VL - 50
JO - Advanced Engineering Informatics
JF - Advanced Engineering Informatics
M1 - 101403
ER -