Nonnegative Weights: Difference between revisions
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== | == Space-Time Tradeoff Improvements == | ||
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Revision as of 14:35, 15 February 2023
Description
The shortest path problem is the problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights of its constituent edges is minimized. Here, the weights are restricted to be nonnegative.
Related Problems
Generalizations: general weights
Subproblem: Nonnegative Integer Weights
Related: General Weights, Second Shortest Simple Path, st-Shortest Path, 1-sensitive (3/2)-approximate ss-shortest paths, 2-sensitive (7/5)-approximate st-shortest paths, 1-sensitive decremental st-shortest paths, 2-sensitive decremental st-shortest paths, Replacement Paths Problem
Parameters
V: number of vertices
E: number of edges
L: maximum absolute value of edge cost
Table of Algorithms
| Name | Year | Time | Space | Approximation Factor | Model | Reference |
|---|---|---|---|---|---|---|
| Bellman–Ford algorithm (Dantzig ) | 1960 | $O( V² logV)$ | $O(E)$ (total) | Exact | Deterministic | Time |
| Dijkstra's algorithm with list (Whiting & Hillier ) | 1960 | $O( V² )$ | $O(V)$ auxiliary | Exact | Deterministic | Time |
| Dijkstra's algorithm with binary heap (Johnson ) | 1977 | $O((E + V) log V)$ | $O(V)$ auxiliary | Exact | Deterministic | Time |
| Dijkstra's algorithm with Fibonacci heap (Fredman & Tarjan ; Fredman & Tarjan 1987) | 1984 | $O(E + V log V)$ | $O(V)$ auxiliary | Exact | Deterministic | Time |
| Gabow's algorithm | 1983 | $O(E logL/log({2}+(E/V)))$ | $O(V+E)$? | Exact | Deterministic | Time |
Time Complexity Graph
_-_Nonnegative_Weights_-_Time.png)
Space Complexity Graph
_-_Nonnegative_Weights_-_Space.png)
Space-Time Tradeoff Improvements
_-_Nonnegative_Weights_-_Pareto_Frontier.png)
References/Citation
https://www.cs.princeton.edu/courses/archive/fall03/cs528/handouts/fibonacci%20heaps.pdf