Algorithm 1: Bellman-Ford(G, c, t) /* graph G, edges costs c¢, destination ¢ 1 S « length-n array /* keeps track of first edge on path 2 M + (n) x (n) array; /* set border cases 3 M[0,] «0; 4 S[t]...

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Algorithm 1: Bellman-Ford(G, c, t)

* graph G, edges costs c¢, destination ¢
1 S « length-n a
ay /* keeps track of first edge on path
2 M + (n) x (n) a
ay;
* set border cases
3 M[0,] «0;
4 S[t] + None;
5 for vin V —t do
6 M0, v] + oo;
7 S[v] + None;
sg fori=1...n—1do
9 for v in V do
* apply recursive formula
10 Mi, v] « M[i — 1,0];
11 for w in Gv] do
12 M + min{M[i, v]; c[v,w] + M[i — 1,w]};
13 if Mli,v] s updated then
14 | So] + w;
* a
ay of least cost path length
15 return Mn — 1,3], S:

bellmanfordclosestnode-luhe30er-unwrsadc.py 1669783828381-fwsbgkpb-kcf1a3yf.png bellmanfordclosestnode-nyp0ifyc-fjj3opnc.py

Answered Same Day Dec 02, 2022

Solution

Vikas answered on Dec 03 2022

49 Votes

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Algorithm 1: Bellman-Ford(G, c, t) /* graph G, edges costs c¢, destination ¢ 1 S « length-n array /* keeps track of first edge on path 2 M + (n) x (n) array; /* set border cases 3 M[0,] «0; 4 S[t]...

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