Decision support in international long-haul freight transportation for the planning of rest periods, breaks and vehicle refueling

In international long-haul freight transportation, truck drivers are often on the road for several consecutive days or even weeks. During their trips, they must comply with the rules on driving time, breaks and rest periods which in the European Union are governed by Regulation (EC) No 561/2006 which entered into force in April 2007. As the regulation has a high influence on the transport durations, it has to be taken into account when planning arrival times at customer locations and choosing among multiple customer time windows. Considering transport costs, a high attention should be paid to fuel costs as fuel is one main cost driver in the road haulage sector. An analysis of diesel price variations across different European countries showed that a significant potential for cutting fuel expenditure can be found in international long-haul freight transportation. Thus, fuel costs and driver rest periods and breaks are two important issues that transport companies have to take into account to be profitable. Dependencies among the corresponding planning tasks suggest a joint consideration. In this thesis, the resulting problem is approached gradually by starting with the isolated consideration of the two subproblems. For the planning of rest periods, breaks and customer time windows, two mixed integer linear programming (MILP) models and solution strategies are proposed. Together with a transformation algorithm they allow to plan driver activities in compliance with Regulation (EC) No 561/2006 for a given sequence of customer locations and other stops to be visited by a vehicle. One of the models considers all rules, including extended rules, while the other takes into account the regular requirements. A special feature is the consideration of "soft" time windows which has not been studied in this context so far. In addition to the mathematical models, a myopic algorithm was developed that can only "see" the route until the next customer stop and the corresponding customer time windows in advance and plans driver activities accordingly. The advantages of the different approaches are evaluated. The refueling subproblem is addressed by extending the standard fuel optimizer model presented by Suzuki (2008, 2009) which takes into account detours to reach gas stations with attractive fuel prices. Additionally to the original version, the consideration of time windows is included. In a short digression, the new MILP model is embedded in the insertion heuristic developed by Solomon (1987) for solving the vehicle routing problem with time windows (VRPTW). A joint consideration of rest periods, breaks and refueling is achieved by merging the MILP models developed for the isolated problems to one model. The solution process for the resulting multicriteria optimization problem with the goals to minimize lateness, completion time and fuel expenditures is described. Additionally, a preprocessing heuristic is proposed which reduces the number of gas stations to be considered along the route of a vehicle and thus the solution space and the computational effort. For each of the models and algorithms presented numerical experiments were conducted. For the extended VRPTW, the well-known Solomon benchmark instances were modified. The other experiments were performed with instances derived from real-world data that include vehicle routes for one week and information on gas stations along the vehicle routes. For future research, the main elements are proposed that together with metaheuristic strategies can be used to develop a heuristic for the combined problem.