An analysis of stochastic shortest path problems
Mathematics of Operations Research
Least Expected Time Paths in Stochastic, Time-Varying Transportation Networks
Transportation Science
A new model for path planning with interval data
Computers and Operations Research
Dynamic routing under recurrent and non-recurrent congestion using real-time ITS information
Computers and Operations Research
Optimal vehicle routing with real-time traffic information
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems
| Hi-index | 0.01 |
Traffic network disruptions lead to significant increases in transportation costs. We consider networks in which a number of links are vulnerable to these disruptions leading to a significantly higher travel time on these links. For these vulnerable links, we consider known link disruption probabilities and knowledge of transition probabilities for recovering from or getting into a disruption. We develop a framework based on dynamic programming in which we formulate and evaluate different known online and offline routing policies. Next to this, we develop computation-time-efficient hybrid routing policies. To test the efficiency of the different routing policies, we develop a test bed of networks based on a number of characteristics and analyze the results in terms of routes, cost performance and calculation times. Our results show that a significant part of the cost reduction can be obtained by considering only a limited part of the network in detail. The performance of our proposed hybrid policy is only slightly worse than the optimal policy.