On-line genetic algorithm for the dynamic vehicle routing problem with real-time time-dependent travel times

In this paper, a dynamic vehicle routing problem with time windows (DVRPTW) was developed in the context of real-time traffic information. The objective of the problem is to minimize the travel time of the vehicles based on a time-dependent model in which the travel speeds are step functions. In order to calculate the forecasted speed, this model is enriched with an exponential smoothing function. We used at same time an on-line genetic algorithm for the route planning. The validation of this approach on benchmarks shows that the real-time traffic information can improve performances of the route planning.