Applications of Greedy Algorithms
- Dijkstra’s shortest path algorithm: Finds the shortest path between two nodes in a graph.
- Kruskal’s minimum spanning tree algorithm: Finds the minimum spanning tree for a weighted graph.
- Huffman coding: Creates an optimal prefix code for a set of symbols based on their frequencies.
- Fractional knapsack problem: Determines the most valuable items to carry in a knapsack with a limited weight capacity.
- Activity selection problem: Chooses the maximum number of non-overlapping activities from a set of activities.
Greedy Algorithm Tutorial – Examples, Application and Practice Problem
Greedy Algorithm is defined as a method for solving optimization problems by taking decisions that result in the most evident and immediate benefit irrespective of the final outcome. It works for cases where minimization or maximization leads to the required solution.
Table of Content
- What is Greedy Algorithm?
- Characteristics of Greedy Algorithm
- Examples of Greedy Algorithm
- Why to use Greedy Approach?
- How does the Greedy Algorithm works?
- Greedy Algorithm Vs Dynamic Programming
- Applications of Greedy Algorithms
- Advantages of Greedy Algorithms
- Disadvantages of the Greedy Approach
- Greedy Algorithm Most Asked Interview Problems
- Frequently Asked Questions on Greedy Algorithm
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