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Research on a robust multi-objective optimization model of gate assignment for hub airport.
- Source :
- Transportation Letters; Jul2018, Vol. 10 Issue 4, p229-241, 13p
- Publication Year :
- 2018
-
Abstract
- Gate assignment is one of the important tasks in the airport. The goal is to appoint an appropriate gate for the arrival or departure flight and ensures the flights are on schedule. So an appropriate and efficient gate assignment model can effectively decrease the flight delays and improve operation efficiency as well as service quality since it plays a major role in increasing revenues. In this paper, the multi-commodity network flow model is analyzed. And a robust multi-objective optimization model of gate assignment based on the objective of minimizing total time for passengers and balancing idle time for each gate is proposed to improve the service level and satisfaction of passengers and utilization rate of gates. The weighting method of linear is used to translate the multi-objective optimization model into the single objective optimization model. And ILOG CPLEX optimizer is used to solve the optimization model of gate assignment in order to obtain the reasonable gate assignment result. The schedule data of 116 flights from Sheyang Taoxian International Airport of China are used to validate the effectiveness of the constructed optimization model. And the multi-objective optimization model is compared with the existing mathematical model of gate assignment. The calculation and comparison results show that the constructed optimization model can significantly improve the assignment efficiency and satisfaction, and balance the utilization rate of gates. So the constructed optimization model of gate assignment can effectively provide a valuable reference for assigning gates. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19427867
- Volume :
- 10
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Transportation Letters
- Publication Type :
- Academic Journal
- Accession number :
- 132000882
- Full Text :
- https://doi.org/10.1080/19427867.2016.1252876