Abstract

Vehicle scheduling problem consists of scheduling a fleet of vehicles to cover a set of tasks at minimum cost. The tasks are given by prescribed time intervals and vehicles are supplied by different depots. The problem is to minimize the number of vehicles used. There are several mathematical models for this problem. The most widely used ones are when the problem is formulated as an integer multi-commodity network flow model.  In this model the optimal schedule is computed by solving a linear integer programming problem. In this talk we overview the most well-known model variants for this problem. After that we present the application of these techniques to the real life problem given by the Szeged transportation company. The results show that these methods can be efficiently used in practice and help finding more efficient schedules for the vehicles. Our experimental analysis shows that about 5-10 percent cost reduction can be realized by using these techniques.

Presentation files