Undirected, General MST: Difference between revisions
(Created page with "{{DISPLAYTITLE:Undirected, General MST (Minimum Spanning Tree (MST))}} == Description == A minimum spanning tree (MST) or minimum weight spanning tree is a subset of the edges of a connected; edge-weighted undirected graph that connects all the vertices together; without any cycles and with the minimum possible total edge weight. Here, there are no restrictions on edge weights or graph density. == Related Problems == Subproblem: Undirected, Dense MST, Undirec...") |
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== Parameters == | == Parameters == | ||
V: number of vertices | |||
E: number of edges | E: number of edges | ||
U: maximum edge weight | |||
U: maximum edge weight | |||
== Table of Algorithms == | == Table of Algorithms == |
Revision as of 12:02, 15 February 2023
Description
A minimum spanning tree (MST) or minimum weight spanning tree is a subset of the edges of a connected; edge-weighted undirected graph that connects all the vertices together; without any cycles and with the minimum possible total edge weight. Here, there are no restrictions on edge weights or graph density.
Related Problems
Subproblem: Undirected, Dense MST, Undirected, Planar MST, Undirected, Integer Weights MST
Related: Undirected, Planar MST, Undirected, Integer Weights MST, Directed (Optimum Branchings), General MST, Directed (Optimum Branchings), Super Dense MST
Parameters
V: number of vertices
E: number of edges
U: maximum edge weight
Table of Algorithms
Name | Year | Time | Space | Approximation Factor | Model | Reference |
---|---|---|---|---|---|---|
Kruskal’s algorithm with demand-sorting | 1991 | $O(Elog(V)$) | $O(E)$ auxiliary | Exact | Deterministic | Time |
Quick Kruskal algorithm | 2006 | $O(Elog(V)$) | $O(E)$ auxiliary | Exact | Deterministic | Time |
Karger; Klein & Tarjan | 1995 | $O(min(V^{2}, ElogV)$) | $O(E)$ auxiliary | Exact | Randomized | Time |
Borůvka's algorithm | 1926 | $O(ElogV)$ | $O(V)$ auxiliary | Exact | Deterministic | |
Prim's algorithm + adjacency matrix searching | 1957 | $O(V^{2})$ | $O(V)$ auxiliary | Exact | Deterministic | Time |
Prim's algorithm + Fibonacci heaps; Fredman & Tarjan | 1987 | $O(E + VlogV)$ | $O(V)$ auxiliary? | Exact | Deterministic | Time |
Kruskal's algorithm | 1956 | $O(ElogE)$ | $O(E)$ auxiliary | Exact | Deterministic | Time |
Yao's algorithm | 1975 | $O(EloglogV)$ | $O(E)$ auxiliary? | Exact | Deterministic | Time |
Cheriton-Tarjan Algorithm | 1976 | $O(EloglogV)$ | $O(E)$ auxiliary? | Exact | Deterministic | Time |
Filter Kruskal algorithm | 2009 | $O(Elog(V))$ | $O(E)$ auxiliary? | Exact | Deterministic | Time |
Chazelle's algorithm | 2000 | $O(E*\alpha(E, V))$ | $O(E)$ auxiliary?? | Exact | Deterministic | Time |
Thorup (reverse-delete) | 2000 | $O(E LogV (loglogV)^{3})$ | $O(E)$ auxiliary? | Exact | Deterministic | Time |
Bader & Cong Parallel Implementation | 2006 | $O(E log(V)$/p) | $O(V)$ total | Exact | Parallel | Time |
Prim's algorithm + binary heap | - | $O(ElogV)$ | $O(V)$ auxiliary? | Exact | Deterministic | |
Fredman & Tarjan | 1987 | $O(E*beta(E, V)$) where beta(m, n) = min(i such that log^(i)(n)≤m/n); this is also $O(E (log-star)$V) | $O(E)$ auxiliary? | Exact | Deterministic | Time |
Gabow et al, Section 2 | 1986 | $O(E*log(beta(E, V)$)) | $O(E)$ auxiliary? | Exact | Deterministic | Time |
Pettie, Ramachandran | 2002 | unknown but optimal | $O(E)$ auxiliary? | Exact | Deterministic | Time |
Time Complexity graph
Space Complexity graph
Pareto Decades graph
References/Citation
https://dl-acm-org.ezproxy.canberra.edu.au/doi/10.1145/505241.505243
https://dl-acm-org.ezproxy.canberra.edu.au/doi/10.1145/505241.505243