Priority Queue is a fundamental data structure in computer science that allows us to store and retrieve elements based on their priority. In a priority queue, each element is associated with a priority value, and elements with higher priority values are dequeued first. In this article, we will explore the various types of priority queues and their characteristics.
1. Binary Heap
A binary heap is one of the most commonly used implementations of a priority queue.
It is a complete binary tree where each node satisfies the heap property. The heap property states that for every node, the key of the parent node is either greater than or equal to its children’s keys.
The binary heap can be represented using an array. The root element is stored at index 0, and for any given node at index i:
- The left child is stored at index (2 * i) + 1
- The right child is stored at index (2 * i) + 2
2. Binomial Heap
A binomial heap is a collection of binomial trees, where each binomial tree follows certain properties.
A binomial tree of order k has exactly 2^k nodes. In a binomial heap, the trees are arranged in a specific order called the “binomial order.” The root of each tree in the binomial heap contains the minimum key value among all the nodes in that tree.
Properties of Binomial Heaps:
- Each binomial tree follows the min-heap property.
- Increasing order of binomial trees in terms of their degrees (number of children).
- There can be at most one binomial tree for any specific degree.
3. Fibonacci Heap
A Fibonacci heap is a collection of min-heap-ordered trees.
It has the advantage of having a very efficient decrease-key operation, which makes it suitable for certain algorithms like Dijkstra’s shortest path algorithm.
The key feature of a Fibonacci heap is the ability to perform melding, which combines two heaps into one in constant time. This operation makes it faster than other priority queue implementations for certain operations.
Properties of Fibonacci Heaps:
- Each node in the heap has a degree (number of children).
- Each node also has a flag indicating whether it has lost a child since the last time it became the child of another node.
- The potential function of a Fibonacci heap is used to ensure amortized constant time complexity for most operations.
4. Pairing Heap
A pairing heap is an unordered tree-based data structure that allows efficient merging and manipulation of heaps.
It achieves simplicity and efficiency by using pairwise merging as its main operation.
In a pairing heap, each node can have an arbitrary number of children, and the tree can be unbalanced. The root of each subtree represents the minimum element in that subtree.
Main Operations on Pairing Heaps:
- Merging: Combining two pairing heaps into one in constant time.
- Insertion: Inserting an element into the heap in logarithmic time complexity.
- Deletion: Removing the minimum element from the heap in logarithmic time complexity.
These are some commonly used types of priority queues in data structures. Each type has its own advantages and disadvantages, and the choice of priority queue depends on the specific requirements of the application.