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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Main Authors: Xi Geng, Minghua Hu
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2020/4731918
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spelling 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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