<--- Back to Details
First PageDocument Content
Network flow / Operations research / Routing algorithms / Network theory / Bellman–Ford algorithm / Shortest path problem / Dynamic programming / Induced path / Maximum flow problem / Mathematics / Graph theory / Theoretical computer science
Date: 2014-01-08 09:09:07
Network flow
Operations research
Routing algorithms
Network theory
Bellman–Ford algorithm
Shortest path problem
Dynamic programming
Induced path
Maximum flow problem
Mathematics
Graph theory
Theoretical computer science

COMS21103 Given a (weighted, directed) graph G and a pair of vertices s and t, we would like to find a shortest path from s to t. A fundamental task with many applications:

Add to Reading List

Source URL: www.cs.bris.ac.uk

Download Document from Source Website

File Size: 1,83 MB

Share Document on Facebook

Similar Documents

EE365: Deterministic Finite State Control  Deterministic optimal control Shortest path problem Dynamic programming Examples

EE365: Deterministic Finite State Control Deterministic optimal control Shortest path problem Dynamic programming Examples

DocID: 1vg0M - View Document

We approach the problem of computing geometric centralities, such as closeness and harmonic centrality, on very large graphs; traditionally this task requires an all-pairs shortest-path computation in the exact case, or

We approach the problem of computing geometric centralities, such as closeness and harmonic centrality, on very large graphs; traditionally this task requires an all-pairs shortest-path computation in the exact case, or

DocID: 1sauD - View Document

We approach the problem of computing geometric centralities, such as closeness and harmonic centrality, on very large graphs; traditionally this task requires an all-pairs shortest-path computation in the exact case, or

We approach the problem of computing geometric centralities, such as closeness and harmonic centrality, on very large graphs; traditionally this task requires an all-pairs shortest-path computation in the exact case, or

DocID: 1rNo2 - View Document

Improving Restoration Success in Mesh Optical Networks Fang Yu 1, Rakesh Sinha2, Dongmei Wang3, Guangzhi Li3, John Strand2, Robert Doverspike2, Charles Kalmanek 3, and Bruce Cortez 2 1 EECS Department, UC Berkeley, Berke

Improving Restoration Success in Mesh Optical Networks Fang Yu 1, Rakesh Sinha2, Dongmei Wang3, Guangzhi Li3, John Strand2, Robert Doverspike2, Charles Kalmanek 3, and Bruce Cortez 2 1 EECS Department, UC Berkeley, Berke

DocID: 1rrH0 - View Document

CS261: A Second Course in Algorithms Lecture #2: Augmenting Path Algorithms for Maximum Flow∗ Tim Roughgarden† January 7, 2016

CS261: A Second Course in Algorithms Lecture #2: Augmenting Path Algorithms for Maximum Flow∗ Tim Roughgarden† January 7, 2016

DocID: 1rn0k - View Document