Optimization of airport bus timetable in cultivation period considering passenger dynamic airport choice under conditions of uncertainty
An airport bus service, which is newly introduced in a multi-airport region, commonly leads to a gradually increasing market share of airports until a new state of equilibrium is reached. With the goal of speeding up and enlarging the increase in market share, this paper proposes a timetable optimization model by incorporating reactions of airport-loyal passengers to bus service quality. The simulation part of the model, which uses cumulative prospect theory to formulate discrete airport choices, results in predicted passenger demand needed in the optimization part. Then a genetic algorithm for multi-objective optimization problems called NSGA-II is applied to solve the model. To illustrate the model, the “Lukou airport-Wuxi” airport bus in China is taken as an example. The results show that the optimized timetables shorten the cultivation period and impel the market share to grow rapidly.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
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Supplemental Notes:
- Abstract reprinted with permission of Elsevier.
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Authors:
- Lu, Jing
- Yang, Zhongzhen
- Timmermans, Harry
- Wang, Wendi
- Publication Date: 2016-6
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: pp 15-30
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Serial:
- Transportation Research Part C: Emerging Technologies
- Volume: 67
- Publisher: Elsevier
- ISSN: 0968-090X
- Serial URL: http://www.sciencedirect.com/science/journal/0968090X
Subject/Index Terms
- TRT Terms: Airport ground transportation; Airports; Buses; Consumer preferences; Market share; Optimization; Passengers; Quality of service; Timetables; Uncertainty
- Uncontrolled Terms: Passenger loyalty
- Geographic Terms: China
- Subject Areas: Aviation; Planning and Forecasting; Public Transportation;
Filing Info
- Accession Number: 01600212
- Record Type: Publication
- Files: TRIS
- Created Date: May 16 2016 2:41PM