A genetic approach to solving the vehicle routing problem with time-dependent travel times

This article relates to the dynamic vehicle routing problem with time windows (DVRPTW) and variable travel times. More precisely, the objective is to take into account the variability of travel times on account of traffic congestion during a day. To reach this objective, we developed an online genetic algorithm to be able to integrate the incidents appearing during the day in the planning of the routes. The objective is to minimize the routing travel time and the lateness for customers. This algorithm is based on a modelling of travel time under the form of speed profiles reflecting traffic congestion. The results show that the variable speed model gives better results than the constant speed model.