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Matthew Maxel

dblp:75/880 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Graph algorithms and graph theory · 93% Algorithms and data structures · 7%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Graph algorithms and graph theory
graph algorithms
0.112007
Finding the k shortest simple paths: A new algorithm and its implementation · ACM Trans. Algorithms 2007
Graph algorithms and graph theory › shortest path
k shortest simple paths
0.112007
Finding the k shortest simple paths: A new algorithm and its implementation · ACM Trans. Algorithms 2007
Graph algorithms and graph theory › graph algorithms › fault-tolerant graph structures › fault-tolerant shortest paths
replacement paths
0.112007
Finding the k shortest simple paths: A new algorithm and its implementation · ACM Trans. Algorithms 2007
Graph algorithms and graph theory
shortest path
0.112007
Finding the k shortest simple paths: A new algorithm and its implementation · ACM Trans. Algorithms 2007
Algorithms and data structures
algorithm engineering
0.012007
Finding the k shortest simple paths: A new algorithm and its implementation · ACM Trans. Algorithms 2007

Methods — techniques the papers use, named apart from their topics

replacement paths algorithm · 0.1optimistic algorithm · 0.1
YearPublicationVenuePosition
2007 Finding the k shortest simple paths: A new algorithm and its implementation
abstract
We describe a new algorithm to enumerate the k shortest simple (loopless) paths in a directed graph and report on its implementation. Our algorithm is based on a replacement paths algorithm proposed by Hershberger and Suri [2001], and can yield a factor Θ( n ) improvement for this problem. But there is a caveat: The fast replacement paths subroutine is known to fail for some directed graphs. However, the failure is easily detected, and so our k shortest paths algorithm optimistically uses the fast subroutine, then switches to a slower but correct algorithm if a failure is detected. Thus, the algorithm achieves its Θ( n ) speed advantage only when the optimism is justified. Our empirical results show that the replacement paths failure is a rare phenomenon, and the new algorithm outperforms the current best algorithms; the improvement can be substantial in large graphs. For instance, on GIS map data with about 5,000 nodes and 12,000 edges, our algorithm is 4--8 times faster. In synthetic graphs modeling wireless ad hoc networks, our algorithm is about 20 times faster.
John Hershberger 0001, Matthew Maxel, Subhash Suri
ACM Trans. Algorithms2
2003 Finding the k Shortest Simple Paths: A New Algorithm and Its Implementation
John Hershberger 0001, Matthew Maxel, Subhash Suri
ALENEX2