This paper examines the value of real-time traffic information to optimal vehicle routing in a nonstationary stochastic network. We present a systematic approach to aid in the implementation of transportation systems integrated with real-time information technology. We develop decision-making procedures for determining the optimal driver attendance time, optimal departure times, and optimal routing policies under time-varying traffic flows based on a Markov decision process formulation. With a numerical study carried out on an urban road network in Southeast Michigan, we demonstrate significant advantages when using this information in terms of total cost savings and vehicle usage reduction while satisfying or improving service levels for just-in-time delivery.

Routing vehicles based on real-time traffic conditions has been shown to significantly reduce travel time, and hence cost, in high-volume traffic situations. However, taking real-time traffic data and transforming them into optimal route decisions are a computational challenge. This is in a large part due to the amount of data available that could be valuable in the route selection. The authors model the dynamic route determination problem as a Markov decision process (MDP) and present procedures for identifying traffic data having no decision-making value. Such identification can be used to reduce the state space of the MDP, thereby improving its computational tractability. This reduction can be achieved by a two-step process. The first is an a priori reduction that may be performed using a stationary deterministic network with upper and lower bounds on the cost functions before the trip begins. The second part of the process reduces the state space further on the nonstationary stochastic road network as the trip optimally progresses. The authors demonstrate the potential computational advantages of the introduced methods based on actual data collected on a road network in southeast Michigan.

One of the major design issues in wireless ATM networks is the support of inter-switch handoffs. An inter-switch handoff occurs when a mobile terminal moves to a new base station connecting to a different switch. Apart from resource allocation at the new base station, inter-switch handoff also requires connection rerouting. With the aim of minimizing the handoff delay while using the network resources efficiently, the two-phase handoff protocol uses path extension for each inter-switch handoff, followed by path optimization if necessary. The objective of this paper is to determine when and how often path optimization should be performed. The problem is formulated as a semi-Markov decision process. Link cost and signaling cost functions are introduced to capture the tradeoff between the network resources utilized by a connection and the signaling and processing load incurred on the network. The time between inter-switch handoffs follows a general distribution. A stationary optimal policy is obtained when the call termination time is exponentially distributed. Numerical results show significant improvement over four other heuristics.