Reactive and Proactive Routing Strategies with Real-Time Traffic Information

This paper deals with routing policies that can be followed by fleet managers in order to minimize the economical and computational cost of providing service under an urban context with real-time traffic information. In particular, we study the dynamic vehicle routing problem with time windows where an initial routing plan can be modified in order to fulfill new customer orders that are received during the execution of a plan. Several routing policies are examined to identify a suitable strategy to assign new customer orders while taking into account the computational effort as well as previous knowledge available about demand. In the computational tests conducted in this paper, a dynamic traffic simulation model has been used to emulate the current traffic conditions providing, at each time interval, estimates of the traffic state on each link of the road network.