binary-heap

In a binary max heap implemented as a binary tree (where each node stores a pointer to its parent, left child, and right child), if you have the pointer to the root of the heap, how would you implement an insert operation? What's supposed to happen is the node first gets inserted as the last element in the last row. For array based, you could append to the array, but for tree based implementation, how would you find the right spot? templatetypedef In this older question , I gave a short algorithm that uses the binary representation of the number k in order to find a way to select the k -th

I am just trying to learn binary heap and have a doubt regarding doing delete operation in binary heap. I have read that we can delete an element from binary heap and we need to reheapify it. But at the following link, it says unavailable: http://en.wikibooks.org/wiki/Data_Structures/Tradeoffs Binary Search AVL Tree Binary Heap (min) Binomial Queue (min) Find O(log n) O(log n) unavailable unavailable Delete element O(log n O(log n) unavailable unavailable I am little confused about it. Thanks in advance for all of the clarifications. Fred Foo Binary heaps and other priority queue structures

In a (max) heap it is easy to find the biggest item in O(1) time, but to actually remove it you need complexity of O(log(n)) . So if the insertion and deletion from a heap is both O(log(n)) , what are the advantages of a heap over binary tree for representing a priority queue? Heaps use less memory. They can be implemented as arrays and thus there is no overhead for storing pointers. (A binary tree CAN be implemented as an array, but there is likely to be many empty "gaps" which could waste even more space than implementing them as nodes with pointers). Heaps are guaranteed to have height of

In my program I need to delete an element from a priority queue that is not at the top. Can that be done? If not, please suggest a way to do so except creating your own heap. The standard priority_queue<T> can be customized through inheritance. It has protected members c and comp that can be referenced in a descendant class. template<typename T> class custom_priority_queue : public std::priority_queue<T, std::vector<T>> { public: bool remove(const T& value) { auto it = std::find(this->c.begin(), this->c.end(), value); if (it != this->c.end()) { this->c.erase(it); std::make_heap(this->c.begin()

As an exercise in Haskell, I'm trying to implement heapsort. The heap is usually implemented as an array in imperative languages, but this would be hugely inefficient in purely functional languages. So I've looked at binary heaps, but everything I found so far describes them from an imperative viewpoint and the algorithms presented are hard to translate to a functional setting. How to efficiently implement a heap in a purely functional language such as Haskell? Edit: By efficient I mean it should still be in O(n*log n), but it doesn't have to beat a C program. Also, I'd like to use purely

I think that I know the answer and the minimum complexity is O(nlogn) . But is there any way that I can make an binary search tree from a heap in O(n) complexity? There is no algorithm for building a BST from a heap in O(n) time. The reason for this is that given n elements, you can build a heap from them in O(n) time. If you have a BST for a set of values, you can sort them in O(n) time by doing an inorder traversal. If you could build a BST from a heap in O(n) time, you could then have an O(n) sorting algorithm by Building the heap in O(n) time, Converting the heap to a BST in O(n) time, and

I have created a binary heap, which represents a priority queue. It's just classical well known algorithm. This heap schedules a chronological sequence of different events ( the sort key is time ). It supports 2 operation: Insert and Remove. Each node's key of the heap is greater than or equal to each of its children. However, adding events with the same key doesn't preserve the order they were added, because each time after Remove or Insert were called, the heap-up and the heap-down procedures break the order. My question is: what should be changed in a classical algorithm to preserve the