Algebraic Cost's Algorithm The maximal weighted matching issue in a weighted network can be solved in a different way using the algorithm attributed to Preis. The following stages make up the algorithm. 1. Input: A weighted graph G = (V, E, w) 2. Output: A maximal weighted matching M of G 3. M ← Ø 4. E ← E 5. V ← V 6. while E = Ø 7. select at random any v ∈ V 8. let e ∈ E be the heaviest edge incident to v 9. M ← M ∪ e 10. V ← V {v} 11. E ← E \ {e and all adjacent edges to e} We'll demonstrate two Python implementation methods for this technique.
Algebraic Cost's Algorithm The maximal weighted matching issue in a weighted network can be solved in a different way using the algorithm attributed to Preis. The following stages make up the algorithm. 1. Input: A weighted graph G = (V, E, w) 2. Output: A maximal weighted matching M of G 3. M ← Ø 4. E ← E 5. V ← V 6. while E = Ø 7. select at random any v ∈ V 8. let e ∈ E be the heaviest edge incident to v 9. M ← M ∪ e 10. V ← V {v} 11. E ← E \ {e and all adjacent edges to e} We'll demonstrate two Python implementation methods for this technique.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Algebraic Cost's
The maximal weighted matching issue in a weighted network can be solved in a different way using the algorithm attributed to Preis. The following stages make up the algorithm.
1. Input: A weighted graph G = (V, E, w)
2. Output: A maximal weighted matching M of G
3. M ← Ø
4. E ← E
5. V ← V
6. while E = Ø
7. select at random any v ∈ V
8. let e ∈ E be the heaviest edge incident to v
9. M ← M ∪ e
10. V ← V {v}
11. E ← E \ {e and all adjacent edges to e}
We'll demonstrate two Python implementation methods for this technique.
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