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'''See Also''' TreeStructures |
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{{{ G = (V,E) }}} |
<<latex($G=(V,E)$)>> |
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The size of input has two components {{{ |V|, |E| }}} |
The size of input has two components <<latex($|V|,|E|$)>> |
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{{{ O(VE) = O(|V|*|E|) }}} |
<<latex($O(VE)=O(|V|*|E|)$)>> |
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To denote the set of vertices in graph G in pseudocode as {{{ V[G] and the edges E[G] }}} |
Denote the set of vertices in graph G in pseudocode as <<latex($V[G]$)>> and the edges <<latex($E[G]$)>> |
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* DecomposingDagIntoStronglyConnectComponents | * Decomposing a graph into its StronglyConnectedComponents |
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* KruskalAlgorithm * PrimAlgorithm |
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Graph Theory
This page contains over view information and links to concepts covered in "Intro to Algorithms" by Cormen, Leiserson & Rivest.
See Also TreeStructures
Notation
A graph is usually specified by:
<<latex($G=(V,E)$)>>
The size of input has two components <<latex($|V|,|E|$)>>
In AsymptoticNotation we abuse the notation for size by writing
<<latex($O(VE)=O(|V|*|E|)$)>>
Denote the set of vertices in graph G in pseudocode as <<latex($V[G]$)>> and the edges <<latex($E[G]$)>>
Chapter 22
Concepts
Applications
Decomposing a graph into its StronglyConnectedComponents
Chapter 23
Minimum Spanning Trees are generally GreedyAlgorithms
Chapter 24-25
- 24: Shortest Path to all vertices from a single vertex
Chapter 26
This general problem arises in many forms and a good algorithm for computer MaxFlow can be used to solve a variety of related problems