Research on efficient and environmentally friendly urban logistics systems based on ITS

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This study presented probabilistic vehicle routing and scheduling with time windows and dynamic vehicle routing and scheduling with time windows.We developed probabilistic vehicle routing and scheduling with time windows model taking into account the variable travel times on network links. The model can calculate penalty of early arrival and delay at customers by estimating the distribution of arrival at customers. The model minimizes the total costs. This model was applied to a test road network. The results showed that probabilistic vehicle routing and scheduling model reduced the total costs of truck operations as well as CO_2 emissions. Therefore. probabilistic vehicle routing and scheduling can be a useful method for efficient and environmentally friendly urban logistics systems.We also developed dynamic vehicle routing and scheduling with time windows model using real time information on travel times. The model can adjust the allocation of trucks to customers and route for visiting customers. Genetic algorithms were used for identifying rapidly the approximate solutions. The model was applied to a test road network. The results showed that probabilistic vehicle routing and scheduling model reduced the total costs of truck operations as well as the total running times. Therefore, the model can contribute to generate benefits not only for freight carriers in terms of cost reduction but also for society at large in terms of alleviating congestion and improving the environment.