A methodology for estimating expected distances between nodes on a network

Transportation, distribution, and logistics professionals often need to estimate the distances that are used for the arc lengths between nodes on a network model. For example, a network model might be representative of roads and cities in which the actual distance from one city to the next may vary depending upon the actual source and destination within each of the respective cities. Hence, estimates for the arc lengths within the network model will contain error. This research presents two new models to estimate these inter-nodal distances for cases in which complete nodal representation of every source and destination is computationally prohibitive.