Airline flight schedules are often affected by sudden disturbance events, causing flights unable to takeoff orlanding as scheduled and resulting in delays for their connecting flights. One of the worst disturbanceevents is Typhoon. If the duration of Typhoon can be accurately forecasted and the flight schedules and thefleet routes can be effectively adjusted, the operation impacts and losses of the carrier would be significantlyreduced. In practice, facing Typhoon disturbance events, most carriers rely on their experiences with theaviation weather forecast data to adjust flight schedules and fleet routes, which is neither efficient noreffective. In particular, the airline network operation is not systematically considered, usually resulting in afeasible but inferior solution. In past studies, most focus on either flight scheduling problems in theplanning stage or real time flight schedule adjustment problems in the operation stage. In this research, theplanning and adjustment of flight schedules in both stages will be included. One is to pre-assign flights toprevent from severe disturbances of stochastic events, as performed in the stage of flight scheduling problems.The other is to adjust flight schedules and fleet routes given the anticipated stochastic disturbance events, asperformed in operation stage of flight adjustment problems. It is rare to find in the past studies that thesetwo problems are integrated into one. Therefore, in this study, based on the system optimization perspectiveand with the objective of minimizing the total cost, we will develop a deterministic flight-reassignmentmodel, a stochastic flight-reassignment model, a simulation framework and a multistage decision process toevaluate the performances of different decisions. The models are expected to be useful tools for thedecision maker to adjust flight schedules and fleet routes in response to typhoon disturbance events.After a preliminary evaluation, the scope of this research is expected to be large, so we propose a three-yearproject. In the first year, considering the operations and constraints of the target airline in practice, we willconstruct a deterministic flight reassignment model based on a precisely disturbed time period of the airport,when no aircraft is allowed for takeoff or landing. In the second year, we will construct a stochastic flightreassignment model based on an imprecisely disturbed time period of the airport. In the third year, we willconduct a simulation analysis with a multistage decision-making process to compare with the performancesof for the application of the two models. We will employ the network flow techniques and mathematicalprogramming to develop all the models with suitable objective functions and constraints based on theproblem characteristics to comply with real operating requirements. All the models are expected to beformulated as a special multiple commodity network flow problem, which is characterized as NP-hard socannot be optimally solved within a reasonable time for realistically large problems. To efficiently solve therealistically large problems that occur in practice, we will develop a solution algorithm for each model byadopting Lagrangian relaxation-based algorithm with subgradient method and suitable meta-heuristicmethods, coupled with the use of the CPLEX software. Finally, to evaluate the models and the solutionalgorithms in practice, we will randomly generate various input data, coupled with the techniques ofsimulation and dynamic decision-making to perform case studies. Conclusions and suggestions will then begiven.
|Effective start/end date||1/08/16 → 31/07/17|
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
- stochastic disturbance event
- flight reassignment
- multistage decision-making
- multiplecommodity network flow problem
- Lagrangian relaxation-based algorithm with subgradientmethod
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