Vehicle Routing and Scheduling Incorporating Shortest Path Model for Dynamic and Stochastic Networks

Abstract

This paper aims at estimating vehicle routing and scheduling which includes dynamic and stochastic elements of travel time on links. In order to consider these elements of travel time, three shortest path models were used. First model is path based on mean travel time by Dijkstra methods (1959), second one is the adaptive least-expected time path by Miller-Hooks (2001) and third one is expected shortest path by Fu and Rillet (1998). Vehicle routing and scheduling were calculated based on link costs by these shortest path models. The deliveries of the vehicle routing and scheduling were simulated and total costs of the delivery were compared. As a result, shortest path models which consider dynamic and stochastic elements outperform the one based on mean travel time for planning vehicle routing and scheduling. Particularly, delay at customers hardly occurred in the expected shortest path.