5 research outputs found
08. Branching Strategies to Improve Regularity of Crew Schedules in Ex-Urban Public Transit
We discuss timetables in ex-urban bus traffic that consist of many trips serviced every day together with some exceptions that do not repeat daily. Traditional optimization methods for vehicle and crew scheduling in such cases usually produce schedules that contain irregularities which are not desirable especially from the point of view of the bus drivers. We propose a solution method which improves regularity while partially integrating the vehicle and crew scheduling problems. The approach includes two phases: first we solve the LP relaxation of a set partitioning formulation, using column generation together with Lagrangean relaxation techniques. In a second phase we generate integer solutions using a new combination of local branching and various versions of follow-on branching. Numerical tests with artificial and real instances show that regularity can be improved significantly with no or just a minor increase of costs
Advanced OR and AI Methods in Transportation
This paper proposes a heuristic solution approach for solving multipledepot integrated vehicle and crew scheduling problem. The basic idea of the method is to first solve independent vehicle and crew scheduling problems separately, and then identify sequences of trips presented in both solutions. Afterwards, the model size is reduced by fixing such sequences before solving the actual multiple-depot integrated vehicle and crew scheduling problem