Turnaround is one of the most critical airport processes. It is defined as the period of time the aircraft is on the ramp between an inbound and outbound flight, and different ground handling operations are performed. Ground handling comprises a set of interrelated services necessary to prepare an aircraft for the next flight. Since ground handling tasks are very interdependent, each operation is a potential source of delays which could be easily propagated to other operations and other airport processes. Moreover, planning decisions about each vehicle required to perform an operation affect the scheduling of other activities and the performance of other resources. The lack of integration of the different activities and an inefficient use of the resources during turnaround are important causes of flight delays. This thesis aims to contribute to the operational efficiency of ground handling facing the problem from a global perspective. Different operations and their interconnections have been considered instead of scheduling each activity in isolation. We introduce a multi-objective approach for scheduling the ground handling vehicles that perform this set of related activities. Solving this problem consists of obtaining a schedule for the vehicles that service aircraft at an airport during one working day. The schedule has to satisfy temporal, precedence, and capacity constraints. Besides obtaining optimized schedules for each activity, it is important to take into account the impact on other tasks. This way, we can integrate the scheduling decisions made for each service and contribute to optimize the overall ground handling process. Two objectives are defined in order to integrate the scheduling decisions : (i) minimizing the waiting time before an operation starts and the total reduction of the corresponding time windows, using the vehicles efficiently; and (ii) minimizing the total completion time of the turnarounds. A new method called Sequence Iterative Method (SIM) has been developed to address the multi-objective problem. With the aim to achieve a more flexible and accurate decision process, a range of solutions representing the best compromise between the two objectives is obtained. The ground handling problem is separated using a workcenter-based decomposition schema. This schema provides a consistent method to solve the complete problem and simplifies the model and the solution process. First, a planning problem is solved and a time window for each operation is calculated according to the temporal and precedence restrictions. One Vehicle Routing Problem with Time Windows (VRPTW) is identified for each type of vehicle involved, which leads to multiple VRPTWs. These are solved individually and decisions made on each routing problem are propagated to the other VRPTWs through reductions on the available time windows. The main features are modeled and implemented in Constraint Programming (CP). Furthermore, CP is used in combination with Variable Neighborhood Descent (VND) and Large Neighborhood Search (LNS) as a part of a hybrid methodology to solve each of the routing problems. The well-known Insertion Heuristics method has been applied to produce a quick first solution which is later improved using the methodology. Finally, a version of the approach is proposed with the goal to allow a more exhaustive exploration to find Pareto solutions. In this case, solutions are obtained using the Insertion Heuristic and just the most promising are improved by the methodology. Two strategies are suggested to determine which solutions are the most promising and these rules can be also employed to guide the decision maker towards the selection of the best schedule to implement.
|Date of Award||22 Jul 2014|
|Supervisor||Daniel Guimarans Serrano (Director) & Juan Jose Ramos Gonzalez (Director)|