Simulated Annealing Method-Based Flight Schedule Optimization in Multiairport Systems
Integrated development and operational collaboration of regional airport groups have the potential to improve capacity and safety and also reduce environmental impacts and operational costs. However, research in multiairport systems (MASs), especially in China, is still in its infancy, with the cons...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2020/4731918 |
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doaj-4f477bfd13e34c4d8d71bd95e1982a032020-11-25T02:52:22ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/47319184731918Simulated Annealing Method-Based Flight Schedule Optimization in Multiairport SystemsXi Geng0Minghua Hu1College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaIntegrated development and operational collaboration of regional airport groups have the potential to improve capacity and safety and also reduce environmental impacts and operational costs. However, research in multiairport systems (MASs), especially in China, is still in its infancy, with the consequences of unbalanced development, inadequate coordination, unclear function partitioning, difficulty in air traffic management, and poor service quality of regional airports. Considering these characteristics influencing effective interaction and collaboration of regional airports, this paper formulates a model to optimize the flight schedules in the MAS with multiple objectives of minimizing the maximum displacement of all flights, the weighted sum of total flight adjustment of each airport, and flight delays. An improved simulated annealing algorithm (SAA) is designed to solve the proposed multiobjective optimization problem. The model is applied to a case of the Beijing-Tianjin-Hebei Airport Group. The computational results demonstrate that the model generates significant reductions in maximum displacement, average displacement, and average delay, compared to the First-Come-First-Served (FCFS) principle. The model proposed in this paper can be used by civil aviation authorities, air navigation service providers, and airlines to facilitate the integrated management of flight schedules in the MAS.http://dx.doi.org/10.1155/2020/4731918 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xi Geng Minghua Hu |
spellingShingle |
Xi Geng Minghua Hu Simulated Annealing Method-Based Flight Schedule Optimization in Multiairport Systems Mathematical Problems in Engineering |
author_facet |
Xi Geng Minghua Hu |
author_sort |
Xi Geng |
title |
Simulated Annealing Method-Based Flight Schedule Optimization in Multiairport Systems |
title_short |
Simulated Annealing Method-Based Flight Schedule Optimization in Multiairport Systems |
title_full |
Simulated Annealing Method-Based Flight Schedule Optimization in Multiairport Systems |
title_fullStr |
Simulated Annealing Method-Based Flight Schedule Optimization in Multiairport Systems |
title_full_unstemmed |
Simulated Annealing Method-Based Flight Schedule Optimization in Multiairport Systems |
title_sort |
simulated annealing method-based flight schedule optimization in multiairport systems |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2020-01-01 |
description |
Integrated development and operational collaboration of regional airport groups have the potential to improve capacity and safety and also reduce environmental impacts and operational costs. However, research in multiairport systems (MASs), especially in China, is still in its infancy, with the consequences of unbalanced development, inadequate coordination, unclear function partitioning, difficulty in air traffic management, and poor service quality of regional airports. Considering these characteristics influencing effective interaction and collaboration of regional airports, this paper formulates a model to optimize the flight schedules in the MAS with multiple objectives of minimizing the maximum displacement of all flights, the weighted sum of total flight adjustment of each airport, and flight delays. An improved simulated annealing algorithm (SAA) is designed to solve the proposed multiobjective optimization problem. The model is applied to a case of the Beijing-Tianjin-Hebei Airport Group. The computational results demonstrate that the model generates significant reductions in maximum displacement, average displacement, and average delay, compared to the First-Come-First-Served (FCFS) principle. The model proposed in this paper can be used by civil aviation authorities, air navigation service providers, and airlines to facilitate the integrated management of flight schedules in the MAS. |
url |
http://dx.doi.org/10.1155/2020/4731918 |
work_keys_str_mv |
AT xigeng simulatedannealingmethodbasedflightscheduleoptimizationinmultiairportsystems AT minghuahu simulatedannealingmethodbasedflightscheduleoptimizationinmultiairportsystems |
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1715364276480245760 |