http://repub.eur.nl/res/aut/4204/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/2318/ 2001-05-01T00:00:00Z Vehicle scheduling is the process of assigning vehicles to a set of predetermined trips with fixed starting and ending times, while minimizing capital and operating costs. This paper considers modeling, algorithmic, and computational aspects of the polynomially solvable case in which there is a single depot and vehicles are identical. A quasiassignment formulation is reviewed and an alternative asymmetric assignment formulation is given. The main contributions of the paper area new two-phase approach which is valid in the case of a special cost structure, an auction algorithm for the quasiassignment problem, a core-oriented approach, and an extensive computational study. New algorithms are compared with the most successful algorithms for the vehicle-scheduling problem, using both randomly generated and real-life data. The new algorithms show a significant performance improvement with respect to computation time. Such improvement can, for example, be very important when this particular vehicle-scheduling problem appears as a subproblem in more complex vehicle- and crew-scheduling problems. http://repub.eur.nl/res/pub/2321/ 1999-01-01T00:00:00Z http://repub.eur.nl/res/pub/1368/ 1995-01-01T00:00:00Z Vehicle scheduling is the process of assigning vehicles to a set of predetermined trips with fixed starting and ending times, while minimizing capital and operating costs. This paper considers the polynomially solvable case in which there is a single depot and one type of vehicle. Several assignment types of formulations are discussed and a new quasi-assignment algorithm is provided. This algorithm is based on an auction algorithm for the linear assignment problem. Furthermore, several ways for dealing with a large number of feasible connections between trips, a bottleneck for vehicle scheduling, are discussed. An important contribution of this paper is a computational study that compares our algorithms with the most successful algorithms for the vehicle scheduling problem, using both randomly generated and real life data. This can serve as a guide for both scientists and practioners. The new quasi-assignment algorithm is shown to be considerably faster for most of the test problems. This improvement in computation time is also very important when this particular vehicle scheduling problem appears as a subproblem in more complex vehicle and crew scheduling problems.