Computing k-shortest path lengths in euclidean networks

In this paper, we examine the problem of finding k-shortest paths between an origin and destination pair when distances are Euclidean. Two versions of a generalized Dijkstra algorithm are compared. Computational results show that the advantage of the adaptive version (measured by total number of permanent labels) grows with both k and the network size. For large networks, the adaptive algorithm exhibits a 100:1 advantage in the number of permanent labels set.