Solving the Dynamic Vehicle Routing Problem Under Traffic Congestion

摘要: This paper proposes a dynamic vehicle routing problem (DVRP) model with nonstationary stochastic travel times under traffic congestion. Depending on the conditions, time between two nodes, particularly in city, may not be proportional to distance and changes both dynamically stochastically over time. Considering this environment, we propose Markov decision process solve adopt rollout-based approach solution, using approximate programming avoid curse of dimensionality. We also investigate how estimate probability distribution arcs which, reflecting reality, are considered consist multiple road segments. Experiments conducted real-world faced by Singapore logistics/delivery company authentic information.