VEHICLE ROUTING AND SCHEDULING USING ITS

This paper presents the results of a stochastic vehicle routing and scheduling (Probabilistic) model, developed to investigate the benefits of incorporating the variable nature of travel times within vehicle routing and scheduling procedures. The benefits of using the Probabilistic model with historical travel time information were estimated using a small hypothetical network. The Probabilistic model performed better than the deterministic (Forecast) model in congested conditions. The benefits of using the Probabilistic instead of the Forecast model increased as actual conditions became more congested, with the Probabilistic model consistently performing better. Significant reductions in both operating and total costs were estimated when the optimal route obtained from the Probabilistic model was used instead of that obtained from the Forecast model when congested conditions were experienced. Lower waiting times were experienced for trucks using the optimal route produced by the Forecast model generally experienced while the Probabilistic model had higher waiting times, except under very congested conditions. For the covering abstract see IRRD E102946.