Binomial Heaps - PowerPoint PPT Presentation

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Binomial Heaps

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Binomial Heaps * On the surface it looks like Binomial Heaps are great if you have no remove mins. But, in this case you need only keep track of the current min item ... – PowerPoint PPT presentation

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Title: Binomial Heaps


1
Binomial Heaps
2
Min Binomial Heap
  • Collection of min trees.

3
Node Structure
  • Degree
  • Number of children.
  • Child
  • Pointer to one of the nodes children.
  • Null iff node has no child.
  • Sibling
  • Used for circular linked list of siblings.
  • Data

4
Binomial Heap Representation
  • Circular linked list of min trees.

Degree fields not shown.
5
Insert 10
  • Add a new single-node min tree to the collection.
  • Update min-element pointer if necessary.

6
Meld
  • Combine the 2 top-level circular lists.
  • Set min-element pointer.

7
Meld
4
1
7
5
3
C
7
9
8
8
Remove Min
  • Empty binomial heap gt fail.

9
Nonempty Binomial Heap
  • Remove a min tree.
  • Reinsert subtrees of removed min tree.
  • Update binomial heap pointer.

10
Remove Min Tree
  • Same as remove a node from a circular list.
  • No next node gt empty after remove.
  • Otherwise, copy next-node data and remove next
    node.

11
Reinsert Subtrees
  • Combine the 2 top-level circular lists.
  • Same as in meld operation.

12
Update Binomial Heap Pointer
  • Must examine roots of all min trees to determine
    the min value.

13
Complexity Of Remove Min
  • Remove a min tree.
  • O(1).
  • Reinsert subtrees.
  • O(1).
  • Update binomial heap pointer.
  • O(s), where s is the number of min trees in final
    top-level circular list.
  • s O(n).
  • Overall complexity of remove min is O(n).

14
Enhanced Remove Min
  • During reinsert of subtrees, pairwise combine min
    trees whose roots have equal degree.

15
Pairwise Combine
Examine the s 7 trees in some order.
Determined by the 2 top-level circular lists.
16
Pairwise Combine
Use a table to keep track of trees by degree.
17
Pairwise Combine
18
Pairwise Combine
Combine 2 min trees of degree 0.
Make the one with larger root a subtree of other.
19
Pairwise Combine
Update tree table.
20
Pairwise Combine
Combine 2 min trees of degree 1.
Make the one with larger root a subtree of other.
21
Pairwise Combine
Update tree table.
22
Pairwise Combine
23
Pairwise Combine
Combine 2 min trees of degree 2.
Make the one with larger root a subtree of other.
24
Pairwise Combine
Combine 2 min trees of degree 3.
Make the one with larger root a subtree of other.
25
Pairwise Combine
Update tree table.
26
Pairwise Combine
27
Pairwise Combine
Create circular list of remaining trees.
28
Complexity Of Remove Min
  • Create and initialize tree table.
  • O(MaxDegree).
  • Done once only.
  • Examine s min trees and pairwise combine.
  • O(s).
  • Collect remaining trees from tree table, reset
    table entries to null, and set binomial heap
    pointer.
  • O(MaxDegree).
  • Overall complexity of remove min.
  • O(MaxDegree s).

29
Binomial Trees
  • Bk is degree k binomial tree.
  • Bk , k gt 0, is

30
Examples
31
Number Of Nodes In Bk
  • Nk number of nodes in Bk.

N0 1
  • Bk , k gt 0, is
  • Nk N0 N1 N2 Nk-1 1
  • 2k.

32
Equivalent Definition
  • Bk , k gt 0, is two Bk-1s.
  • One of these is a subtree of the other.

33
Nk And MaxDegree
  • N0 1
  • Nk 2Nk-1
  • 2k.
  • If we start with zero elements and perform
    operations as described, then all trees in all
    binomial heaps are binomial trees.
  • So, MaxDegree O(log n).
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