Print Email Facebook Twitter A greedy approach to the minimisation of deviations of the dynamic vehicle routing problem with electric taxiing systems Title A greedy approach to the minimisation of deviations of the dynamic vehicle routing problem with electric taxiing systems: Master of Science Thesis Author Tindemans, Bas (TU Delft Aerospace Engineering) Contributor Mitici, M.A. (mentor) Zoutendijk, M. (graduation committee) Snellen, M. (graduation committee) Bombelli, A. (graduation committee) Degree granting institution Delft University of Technology Programme Aerospace Engineering Date 2021-10-07 Abstract In order to reduce aircraft emissions during on-ground operations, electric taxiing systems (ETS) have been intensively researched to take over or assist in part of the taxiing phase of a flight. One of these ETS is the TaxiBot, deployed by Smart Airport Systems (SAS). While a number of papers have been researching this vehicle routing problem (VRP) in order to minimise costs, fuel consumption or another metric, most research uses deterministic input data. However, sudden changes are inevitable, disrupting the resulting schedule. In this paper, we propose both a strategic model and a tactical model for airport surface movement, taking into account stochastic delays to the flight schedule. The subsequent tactical schedule can be produced with only little deviations from the strategic schedule. The tactical model can be generated in the order of seconds, making it useful for real-life traffic management decision support systems. We found that the tactical schedule does not worsen remarkably. Still 47.9% of the flights can be towed by a TaxiBot, which was 48.5% in the strategic schedule. Different case studies have been performed in order to determine the effect of e.g. the size of the flight schedule and the number of TaxiBots used, on the aircraft taxiing coverage and TaxiBot efficiency. With this, both busy and calm days, now and in the near future are assessed and the optimum number of TaxiBots necessary can be determined. An upper limit is reached at an asymptote starting from 34 TaxiBots, while a lower limit is dependent on a trade-off between flight coverage and spare TaxiBot capacity. Subject Electric Taxiing SystemsTaxiBotVehicle Routing ProblemFleet Scheduling AssignmentGreedy ApproachDynamic & StochasticDisruption Management To reference this document use: http://resolver.tudelft.nl/uuid:6f5e960f-796d-476a-a738-ea92d2ce1526 Embargo date 2021-10-08 Part of collection Student theses Document type master thesis Rights © 2021 Bas Tindemans Files PDF Thesis_project_Bas_Tindem ... 9_2021.pdf 14.12 MB Close viewer /islandora/object/uuid:6f5e960f-796d-476a-a738-ea92d2ce1526/datastream/OBJ/view