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Lecture 6 Shortest Path Problem. s t Dynamic Programming.

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Presentation on theme: "Lecture 6 Shortest Path Problem. s t Dynamic Programming."— Presentation transcript:

1 Lecture 6 Shortest Path Problem

2 s t

3 Dynamic Programming

4 Dijkstra’s Algorithm is motivated from a way to implement of this dynamic programming.

5 Dynamic Programming

6 Lemma Proof

7 Theorem 2 -1 2 1

8 Counterexample

9 Smart Implementation

10 An Example 1 2 3 4 5 6 2 4 2 1 3 4 2 3 2 Initialize 1 0      Select the node with the minimum temporary distance label.

11 Update Step 2 3 4 5 6 2 4 2 1 3 4 2 3 2 2 4 0      1

12 Choose u such that N_(u) S 1 3 4 5 6 2 4 2 1 3 4 2 3 2 2 4 0 2   

13 Update Step 1 2 3 4 5 6 2 4 2 1 3 4 2 3 2 2 4 6 4 3 0    The predecessor of node 3 is now node 2

14 Choose u Such That N_(u) S 1 24 5 6 2 4 2 1 3 4 2 3 2 2 3 6 4 0  3

15 Update 1 24 5 6 2 4 2 1 3 4 2 3 2 0 d(5) is not changed. 3 2 3 6 4 

16 Choose u s.t. N_(u) S 1 24 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4  5

17 Update 1 24 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4  5 d(4) is not changed 6

18 Choose u s.t. N_(u) S 1 2 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4

19 Update 1 2 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4 d(6) is not updated

20 Choose u s.t. N_(u) S 1 2 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4 6 There is nothing to update

21 End of Algorithm 1 2 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4 6 All nodes are now permanent The predecessors form a tree The shortest path from node 1 to node 6 can be found by tracing back predecessors

22 Dijkstra’s Algorithm

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24 Lemma

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26 Proof of Lemma s u w S T

27 Theorem

28 Counterexample 3 -1 -2 2 1

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37 Dijkstra’s Algorithm

38 An Example 1 2 3 4 5 6 2 4 2 1 3 4 2 3 2 Initialize 1 0      Select the node with the minimum temporary distance label.

39 Update Step 2 3 4 5 6 2 4 2 1 3 4 2 3 2 2 4 0      1

40 Choose Minimum Temporary Label 1 3 4 5 6 2 4 2 1 3 4 2 3 2 2 4 0 2   

41 Update Step 1 2 3 4 5 6 2 4 2 1 3 4 2 3 2 2 4 6 4 3 0    The predecessor of node 3 is now node 2

42 Choose Minimum Temporary Label 1 24 5 6 2 4 2 1 3 4 2 3 2 2 3 6 4 0  3

43 Update 1 24 5 6 2 4 2 1 3 4 2 3 2 0 d(5) is not changed. 3 2 3 6 4 

44 Choose Minimum Temporary Label 1 24 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4  5

45 Update 1 24 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4  5 d(4) is not changed 6

46 Choose Minimum Temporary Label 1 2 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4

47 Update 1 2 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4 d(6) is not updated

48 Choose Minimum Temporary Label 1 2 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4 6 There is nothing to update

49 End of Algorithm 1 2 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4 6 All nodes are now permanent The predecessors form a tree The shortest path from node 1 to node 6 can be found by tracing back predecessors

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60 Dijkstra’s Algorithm with simple buckets (also known as Dial’s algorithm)

61 An Example 1 2 3 4 5 6 2 4 2 1 3 4 2 3 2 Initialize distance labels 1 0      Select the node with the minimum temporary distance label. 01234567 1  2 3 4 5 6 Initialize buckets.

62 Update Step 01234567 1  2 3 4 5 6 23 2 3 4 5 6 2 4 2 1 3 4 2 3 2 2 4 0      1

63 Choose Minimum Temporary Label 01234567  4 5 6 23 Find Min by starting at the leftmost bucket and scanning right till there is a non-empty bucket. 1 3 4 5 6 2 4 2 1 3 4 2 3 2 2 4 0 2   

64 Update Step 1 2 3 4 5 6 2 4 2 1 3 4 2 3 2 2 4 6 4 3 0    01234567  4 5 6 23 3 4 5

65 Choose Minimum Temporary Label 1 24 5 6 2 4 2 1 3 4 2 3 2 2 3 6 4 0  3 01234567  6 3 45 Find Min by starting at the leftmost bucket and scanning right till there is a non-empty bucket.

66 Update 1 24 5 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4  01234567  6 3 45

67 Choose Minimum Temporary Label 1 24 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4  5 01234567  6 45

68 Update 1 24 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4  5 6 01234567  6 45 6

69 Choose Minimum Temporary Label 1 2 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4 01234567 4 6

70 Update 1 2 6 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4 01234567 4 6

71 Choose Minimum Temporary Label 1 2 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4 6 01234567 6 There is nothing to update

72 End of Algorithm 1 2 2 4 2 1 3 4 2 3 2 0 3 2 3 6 4 5 6 4 6 All nodes are now permanent The predecessors form a tree The shortest path from node 1 to node 6 can be found by tracing back predecessors

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76 Implementations With min-priority queue, Dijkstra algorithm can be implemented in time With Fibonacci heap, Dijkstra algorithm can be implemented in time With Radix heap, Dijkstra algorithm can be implemented in time


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