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All Pair Shortest Path
Floyd’s Algorithm
The Floyd’s Algorithm
The Floyd–Warshall algorithm is a graph
analysis algorithm for finding shortest paths in a
weighted graph with positive or negative edge
weights.
It is also known as
Floyd's algorithm
Roy–Warshall algorithm
Roy–Floyd algorithm
The WFI algorithm
Consider the following graph
Loop
Edge
Vertex
Weight of the
edge
Step 1: Remove all the loops.
Note! Any edge that starts and ends at the same vertex is a loop.
Step 2: Remove all parallel edges between two
vertices leaving only the edge with the smallest
weight.
Step 3: Create a distance and sequence table.
How we will proceed
•To find the shortest path between any two nodes we
will draw two tables namely, Distance Table (D) and
Sequence Table (S).
•We can also refer these tables as matrix.
•The Distance table (D) will hold distance between any
two vertices.
•The Sequence table (S) will hold the name of the
vertices that will help in finding the shortest path
between any two vertices.
•If a graph has k vertices then our table D and S will
have k rows and k columns.
•We will use the iterative method to solve the problem.
Notations we will be using
k = Iteration number
Dk = Distance table in kth iteration
Sk = Sequence table in kth iteration
dij = The distance between vertex i and j
There are 4 vertices in the graph
so, our tables (Distance and Sequence) will
have 4 rows and 4 columns.
Distance table D
This table holds the weight of the respective edges
connecting vertices of the graph. So, if there in an edge
u --> v connecting vertex u to vertex v and having
weight w then we will fill the distance table D[u][v] =
w. If there is no edge connecting any two vertex u to v
then in that case we will fill D[u][v] = INFINITY.
Sequence table S
This table holds the vertex that will be used to find
the shortest path to reach from vertex u to vertex v.
From the graph above we will get the following
sequence table.
From the graph above we will get the following
distance table.
Distance table
D0 1 2 3 4
1 - 5 1 2
2 5 - 3 INF
3 1 3 - 4
4 2 INF 4 -
Sequence table
From the graph above we will get the following
sequence table.
S0 1 2 3 4
1 - 2 3 4
2 1 - 3 4
3 1 2 - 4
4 1 2 3 -
Important Condition
We will fill the cell Cij in distance table Dk using the
following condition.
Is dij > dik + dkj [in distance table Dk-1]
If YES then fill the cell Cij in Dk table with the
value dik + dkj of Dk-1 table
If NO then fill the cell Cij in Dk table with the
value dij of Dk-1 table
where
i = row number
j = column number
k = iteration number
i.e., we will always fill the cell Cij in Dk table with the smallest
value.
Note! If a graph has N vertices then we will be iterating N times.
The graph has 4 vertices so, we will be iterating 4 times.
Solution
D4 1 2 3 4
1 - 4 1 2
2 4 - 3 6
3 1 3 - 3
4 2 6 3 -
S4 1 2 3 4
1 - 3 3 4
2 3 - 3 3
3 1 2 - 1
4 1 3 1 -
And the following sequence table
After completing the 4 iterations we
will get the following distance array.
And the required shortest paths.
Source vertex (i) Destination vertex (j) Distance Shortest path
1 2 4 1->3->2
1 3 1 1->3
1 4 2 1->4
2 3 3 2->3
2 4 6 2->3->1->4
3 4 3 3->1->4
THANK YOU

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(floyd's algm)

  • 1. All Pair Shortest Path Floyd’s Algorithm
  • 2. The Floyd’s Algorithm The Floyd–Warshall algorithm is a graph analysis algorithm for finding shortest paths in a weighted graph with positive or negative edge weights. It is also known as Floyd's algorithm Roy–Warshall algorithm Roy–Floyd algorithm The WFI algorithm
  • 3. Consider the following graph Loop Edge Vertex Weight of the edge
  • 4. Step 1: Remove all the loops. Note! Any edge that starts and ends at the same vertex is a loop.
  • 5. Step 2: Remove all parallel edges between two vertices leaving only the edge with the smallest weight. Step 3: Create a distance and sequence table.
  • 6. How we will proceed •To find the shortest path between any two nodes we will draw two tables namely, Distance Table (D) and Sequence Table (S). •We can also refer these tables as matrix. •The Distance table (D) will hold distance between any two vertices. •The Sequence table (S) will hold the name of the vertices that will help in finding the shortest path between any two vertices. •If a graph has k vertices then our table D and S will have k rows and k columns. •We will use the iterative method to solve the problem.
  • 7. Notations we will be using k = Iteration number Dk = Distance table in kth iteration Sk = Sequence table in kth iteration dij = The distance between vertex i and j There are 4 vertices in the graph so, our tables (Distance and Sequence) will have 4 rows and 4 columns.
  • 8. Distance table D This table holds the weight of the respective edges connecting vertices of the graph. So, if there in an edge u --> v connecting vertex u to vertex v and having weight w then we will fill the distance table D[u][v] = w. If there is no edge connecting any two vertex u to v then in that case we will fill D[u][v] = INFINITY. Sequence table S This table holds the vertex that will be used to find the shortest path to reach from vertex u to vertex v. From the graph above we will get the following sequence table.
  • 9. From the graph above we will get the following distance table. Distance table D0 1 2 3 4 1 - 5 1 2 2 5 - 3 INF 3 1 3 - 4 4 2 INF 4 -
  • 10. Sequence table From the graph above we will get the following sequence table. S0 1 2 3 4 1 - 2 3 4 2 1 - 3 4 3 1 2 - 4 4 1 2 3 -
  • 11. Important Condition We will fill the cell Cij in distance table Dk using the following condition. Is dij > dik + dkj [in distance table Dk-1] If YES then fill the cell Cij in Dk table with the value dik + dkj of Dk-1 table If NO then fill the cell Cij in Dk table with the value dij of Dk-1 table where i = row number j = column number k = iteration number i.e., we will always fill the cell Cij in Dk table with the smallest value. Note! If a graph has N vertices then we will be iterating N times. The graph has 4 vertices so, we will be iterating 4 times.
  • 12. Solution D4 1 2 3 4 1 - 4 1 2 2 4 - 3 6 3 1 3 - 3 4 2 6 3 - S4 1 2 3 4 1 - 3 3 4 2 3 - 3 3 3 1 2 - 1 4 1 3 1 - And the following sequence table After completing the 4 iterations we will get the following distance array.
  • 13. And the required shortest paths. Source vertex (i) Destination vertex (j) Distance Shortest path 1 2 4 1->3->2 1 3 1 1->3 1 4 2 1->4 2 3 3 2->3 2 4 6 2->3->1->4 3 4 3 3->1->4