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Priority Queue and Binary Heap Neil Tang 02/12/2008

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1 Priority Queue and Binary Heap Neil Tang 02/12/2008
CS223 Advanced Data Structures and Algorithms

2 CS223 Advanced Data Structures and Algorithms
Class Overview Priority queue Binary heap Heap operations: insert, deleteMin, de/increaseKey, delete, buildHeap Application CS223 Advanced Data Structures and Algorithms

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Priority Queue A priority queue is a queue in which each element has a priority and elements with higher priorities are supposed to be removed before the elements with lower priorities. CS223 Advanced Data Structures and Algorithms

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Possible Solutions Linked list: Insert at the front (O(1)) and traverse the list to delete (O(N)). Linked list: Keep it always sorted. traverse the list to insert (O(N)) and delete the first element (O(1)). Binary search tree CS223 Advanced Data Structures and Algorithms

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Binary Heap A binary heap is a binary tree that is completely filled, with possible exception of the bottom level and in which for every node X, the key in the parent of X is smaller than (or equal to) the key in X. CS223 Advanced Data Structures and Algorithms

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Binary Heap A complete binary tree of height h has between 2h and 2h+1 -1 nodes. So h = logN. For any element in array position i, its left child in position 2i and the right child is in position (2i+1), and the parent is in i/2. CS223 Advanced Data Structures and Algorithms

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Insert 14 CS223 Advanced Data Structures and Algorithms

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Insert (Percolate Up) Time complexity: O(logN) CS223 Advanced Data Structures and Algorithms

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deleteMin CS223 Advanced Data Structures and Algorithms

10 deleteMin (Percolate Down)
Time complexity: O(logN) CS223 Advanced Data Structures and Algorithms

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Other Operations decreaseKey(p,) increaseKey(p, ) delete(p)? delete(p)=decreaseKey(p,)+deleteMin() CS223 Advanced Data Structures and Algorithms

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buildHeap CS223 Advanced Data Structures and Algorithms

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buildHeap CS223 Advanced Data Structures and Algorithms

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buildHeap CS223 Advanced Data Structures and Algorithms

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buildHeap Theorem: For the perfect binary tree of height 2h+1-1 nodes the sum of the heights of the nodes is 2h+1-1-(h+1). Time complexity: 2*(2h+1-1-(h+1)) = O(N). CS223 Advanced Data Structures and Algorithms

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Applications Problem: find the kth smallest element. Algorithm: buildHeap, then deleteMin k times. Time complexity: O(N+klogN) = O(NlogN). CS223 Advanced Data Structures and Algorithms

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Applications Problem: find the kth largest element. Algorithm: buildHeap with the first k elements, check the rest one by one. In each step, if the new element is larger, deleteMin and insert the new one. Time complexity: O(k+(N-k)logk) = O(NlogN). CS223 Advanced Data Structures and Algorithms


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