A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Abstract-The Vehicle Routing Problem with Time Windows (VRPTW) is an important logistics problem which in the realworld appears to be multi-objective. Most research in this area has been carried out using classic datasets designed for the single-objective case, like the well-known Solomon's problem instances. Some unrealistic assumptions are usually made when using these datasets in the multi-objective case (e.g. assuming that one unit of travel time corresponds to one unit of travel distance). Additionally, there is no common VRPTW multiobjective oriented framework to compare the performance of algorithms because different implementations in the literature tackle different sets of objectives. In this work, we investigate the conflicting (or not) nature of various objectives in the VRPTW and show that some of the classic test instances are not suitable for conducting a proper multi-objective study. The insights of this study have led us to generate some problem instances using data from a real-world distribution company. Experiments in these new dataset using a standard evolutionary algorithm (NSGA-II) show stronger evidence of multi-objective features. Our contribution focuses on achieving a better understanding about the multi-objective nature of the VRPTW, in particular the conflicting relationships between 5 objectives: number of vehicles, total travel distance, makespan, total waiting time, and total delay time.

Abstract. There is a variety of methods for ranking objectives in multiobjective optimization and some are difficult to define because they require information a priori (e.g. establishing weights in a weighted approach or setting the ordering in a lexicographic approach). In manyobjective optimization problems, those methods may exhibit poor diversification and intensification performance. We propose the Dynamic Lexicographic Approach (DLA). In this ranking method, the priorities are not fixed, but they change throughout the search process. As a result, the search process is less liable to get stuck in local optima and therefore, DLA offers a wider exploration in the objective space. In this work, DLA is compared to Pareto dominance and lexicographic ordering as ranking methods within a Discrete Particle Swarm Optimization algorithm tackling the Vehicle Routing Problem with Time Windows.

Commercial airports are under increasing pressure to comply with the Eurocontrol Collaborative Decision Making (CDM) initiative, to ensure that information is passed between stakeholders, integrate automated decision support or make predictions. These systems can also aid effective operations beyond the airport by communicating scheduling decisions to other relevant parties, such as Eurocontrol, for passing on to downstream airports and enabling overall airspace improvements.One of the major CDM components is aimed at producing the target take-off times and target startup-approval times, i.e. scheduling when the aircraft should push back from the gates and start their engines and when they will take off. For medium-sized airports, a common choice for this is a "Pre-Departure Sequencer" (PDS). In this paper, we describe the design and requirements challenges which arose during our development of a PDS system for medium sized international airports. Firstly, the scheduling problem is highly dynamic and event driven. Secondly, it is important to end-users that the system be predictable and, as far as possible, transparent in its operation, with decisions that can be explained. Thirdly, users can override decisions, and this information has to be taken into account. Finally, it is important that the system is as fair as possible for all users of the airport, and the interpretation of this is considered here. Together, these factors have influenced the design of the PDS system which has been built to work within an existing large system which is being used at many airports.