SIAM Journal on Computing
Fast Estimation of Diameter and Shortest Paths (Without Matrix Multiplication)
SIAM Journal on Computing
All-Pairs Almost Shortest Paths
SIAM Journal on Computing
Journal of Algorithms
Computing almost shortest paths
Proceedings of the twentieth annual ACM symposium on Principles of distributed computing
Erratum to "Vickrey Pricing and Shortest Paths: What is an Edge Worth?"
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Vickrey Prices and Shortest Paths: What is an Edge Worth?
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
A new approach to all-pairs shortest paths on real-weighted graphs
Theoretical Computer Science - Special issue on automata, languages and programming
Journal of the ACM (JACM)
On the difficulty of some shortest path problems
ACM Transactions on Algorithms (TALG)
Oracles for Distances Avoiding a Failed Node or Link
SIAM Journal on Computing
A New Combinatorial Approach for Sparse Graph Problems
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I
Replacement paths and k simple shortest paths in unweighted directed graphs
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
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We present the first approximation algorithm for finding the $k$ shortest simple paths connecting a pair of vertices in a weighted directed graph that breaks the barrier of $mn$. It is deterministic and has a running time of $O(k(m\sqrt{n}+n^{3/2}\log n))$, where $m$ is the number of edges in the graph and $n$ is the number of vertices. Let $s,t\in V$; the length of the $i$th simple path from $s$ to $t$ computed by our algorithm is at most $\frac{3}{2}$ times the length of the $i$th shortest simple path from $s$ to $t$. The best algorithms for computing the exact $k$ shortest simple paths connecting a pair of vertices in a weighted directed graph are due to Yen [Management Sci., 17 (1970/1971), pp. 712-716] and Lawler [Management Sci., 18 (1971/1972), pp. 401-405]. The running time of their algorithms, using modern data structures, is $O(k(mn+n^2\log n))$. Both algorithms are from the early 70s. Although this problem and other variants of the $k$ shortest path problem has drawn a lot of attention during the last three and a half decades, the $O(k(mn+n^2\log n))$ bound is still unbeaten.