We address the robust weekly aircraft routing and retiming problem, which requires determining weekly schedules for a heterogeneous fleet that maximizes the aircraft on-time performance, minimizes the total delay, and minimizes the number of delayed passengers. In this effort, we make the following contributions:
- We propose a compact mixed-integer nonlinear programming (MINP) model to solve the robust weekly aircraft maintenance routing problem.
- We apply the Reformulation-Linearization Technique (RLT) of Sherali and Adams, 1990, Sherali and Adams, 1994 to provide an equivalent mixed-integer linear programming formulation than can be solved using a commercial solver.
- We describe a hybrid optimization-simulation approach that delivers robust aircraft routes having enhanced on-time performance, while accommodating maintenance constraints and stochastic . The proposed approach combines mixed-integer programming with Monte-Carlo simulation to derive robust aircraft schedules.
- We perform an extensive computational study using instances based on data provided by a major international airline, and having up to 3387 flights and 164 aircraft. The quality of the proposed solutions is assessed using SimAiras a simulation tool).
Using the simulation software SimAir to assess the robustness of the solutions produced by our approach in comparison with that for the original solutions implemented by the airline, we found that on-time performance was improved by 9.8–16.0%, cumulative delay was reduced by 25.4–33.1%, and the number of delayed passengers was reduced by 8.2–51.6%.
Collected and summarized from the source below by Ta Ngoc Diep: https://db.vista.gov.vn:2095/science/article/pii/S0968090X17301912