Aeronautical revenues optimisation model (AROM) for regional airports via airside operations stochastic baseline matrix analysis / Wan Mazlina Wan Mohamed

Wan Mohamed, Wan Mazlina (2016) Aeronautical revenues optimisation model (AROM) for regional airports via airside operations stochastic baseline matrix analysis / Wan Mazlina Wan Mohamed. PhD thesis, Universiti Teknologi MARA.

[img]
Preview
Text
TP_WAN MAZLINA WAN MOHAMED EM 16_5.pdf

Download (7MB) | Preview

Abstract

Maximising revenues is one of the greatest challenges of regional airports especially after the introduction of deregulation and privatisation of airports with the increase of aggressive competition in the markets. The calculation of aeronautical revenues generation has always been considered as a straightforward method and airport managers generally overlooked on the importance of daily operational factors such as the different flight services offered at the airports, the type of aircraft airlines utilised, time of the day the flight arrives or departs, and the number of passengers the airlines ferry in and out of their airport, types of destination and how these factors influence the generation of aeronautical revenues for their airport. The first objective of this research is to measure the airside operation factors that influence the generation of aeronautical revenues deterministically. The influential variables were determined through literature reviews and case studies of regional airports in the Netherlands and Malaysia, and were validated with regression analysis. Preliminary model was developed based on the determinants and the model was analysed using Bayesian Network theory. Thus, the research is also geared towards developing a baseline matrix using stochastic approach to analyse the effect of airside operation factors on aeronautical revenues generation as the second objective. The next objective concerns with the formulation of mathematical optimisation algorithm known as Aeronautical Revenue Optimisation Model (AROM) to generate maximum aeronautical revenues for regional airport in line with the objectives of the airport. Finally, the research embarks on developing a graphical user interface (GUI) tool based on the model to estimate the possible potential aeronautical revenues that could be generated which will be useful for airport managers in their decision making. The GUI for AROM is a user friendly tool which allows airport managers to key-in the main input parameters such as mode of operations (arrival or departure), traffic types (Schedule, Business, Charter, etc.), flights details (day or night, weekday or weekend, number of passengers, international or domestic), fleet types (aircraft weight and engine type) and type of flights (domestic or international) in order to determine the composition offlight operations that produces optimum aeronautical revenues that could be achieved. Results obtained show that the maximum revenue achieved is based on flights composition, which is more focused towards certain types of traffic types with higher frequency for each of them in contrast to the current practise of offering small number of all sorts of traffic types. The model developed in this research is flexible; it allows decision makers to set the upper bound of flight constraints. The model can also be extended to include bigger sets of flight details, for example, to have day, evening and night flight instead of just day and night. Aside from that, the parameter can also be generalised such as to consider all international flights instead of domestic and international. The traffic types can also be adjusted to include shorter or longer list of traffic types to suit the airport's services.

Item Type: Thesis (PhD)
Uncontrolled Keywords: Aeronautical; Airside operations; Stochastic baseline
Subjects: T Technology > TL Motor vehicles. Aeronautics. Astronautics > Aeronautics. Aeronautical engineering
T Technology > TL Motor vehicles. Aeronautics. Astronautics > Aeronautics. Aeronautical engineering > Mechanics of flight: Aerodynamics
Divisions: Faculty of Mechanical Engineering
Depositing User: Staf Pendigitan 2
Date Deposited: 18 Aug 2017 07:30
Last Modified: 18 Aug 2017 07:30
URI: http://ir.uitm.edu.my/id/eprint/17634

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year