What is Greedy Algorithm?
A greedy algorithm is a problem-solving technique that makes the best local choice at each step in the hope of finding the global optimum solution. It prioritizes immediate benefits over long-term consequences, making decisions based on the current situation without considering future implications. While this approach can be efficient and straightforward, it doesn’t guarantee the best overall outcome for all problems.
However, it’s important to note that not all problems are suitable for greedy algorithms. They work best when the problem exhibits the following properties:
- Greedy Choice Property: The optimal solution can be constructed by making the best local choice at each step.
- Optimal Substructure: The optimal solution to the problem contains the optimal solutions to its subproblems.
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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