In a lecture the professor said that for every minimum spanning tree T of G there is an execution of the algorithm of Kruskal which delivers T as a result. ( Input is G). The algorithm he was supposedly talking about is: Kruskal() Precondition. N = (G, cost) is a connected network with n = |V| node and m = |E| ≥ n − 1 edges.All edges of E are uncolored. postcondition: All edges are colored. The green-colored edges together with V form one MST by N. Grand Step 1: Sort the edges of E in increasing weight: e1 , e2, . . . , em Grand step 2: For t = 0.1, . . . , m − 1 execute: Apply Kruskal's coloring rule to the et+1 edge i dont really understand this statement or how it is done. can someone explain me what he meant?
In a lecture the professor said that for every minimum spanning tree T of G there is an execution of the
The algorithm he was supposedly talking about is:
Kruskal()
Precondition. N = (G, cost) is a connected network with n = |V| node and m = |E| ≥ n − 1 edges.All edges of E are uncolored.
postcondition: All edges are colored. The green-colored edges together with V form one MST by N.
Grand Step 1: Sort the edges of E in increasing weight: e1 , e2, . . . , em
Grand step 2: For t = 0.1, . . . , m − 1 execute: Apply Kruskal's coloring rule to the et+1 edge
i dont really understand this statement or how it is done. can someone explain me what he meant?
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