| dc.description.abstract | The setting of a good flight schedule for an airline not only has to consider its fleet supply, related operations and market share in competition, but also has to consider the uncertainty of the market demand in actual operations. Most of the past research on short-term flight scheduling used the draft timetable and an average passenger demand as input to produce the final timetable and schedule, neglecting the variation of daily passenger demands in actual operations. Although a scheduling model was recently established to deal with variable demands under market competitions, the daily market demand was still assumed fixed in the model, neglecting the stochastic characteristics of daily passenger demands in actual operations, which could affect the optimal fleet routes and timetables. If the market demand is wildly changed in daily operations, then the original schedule could be disturbed to lose its optimality. In the past, the effect of the stochastic disturbance on the optimally planned schedule was rarely researched in either practices or academics. Considering the stochastic characteristics of daily market demands in actual operations, in this research, on the basis of the airline’s perspective, we developed a stochastic-demand scheduling model, with the objective of maximizing the carrier profit, subject to the real operating constraints. The model is expected to be a useful planning tool for airlines to solve their optimal fleet routes and timetables in their short-term operations.
We employed network flow techniques to construct the model, which will include multiple passenger and fleet-flow time-space networks in order to formulate the flows of passengers and aircraft in the dimensions of time and space. Some side constraints will be set between the passenger and fleet-flow time-space networks according to the real operating requirements. The model is expectedly formulated as a nonlinear multiple commodity network flow problem that is characterized as an NP-hard problem. We employed simulation techniques, coupled with a mathematical programming solver, to develop a simulation-based heuristic to solve the problem. To evaluate the stochastic-demand scheduling model and the solution method under stochastic demands in actual operations, we developed a simulation-based evaluation method. Finally, to test the model, the solution method and the evaluation method in practice, we will perform a case study on personal computers, using real operating data from a major Taiwan airline, with the assistance of C computer programs and the mathematical programming solver, CPLEX. Conclusions and suggestions will then be given. | en_US |