"Greedy Method finds out of many options, but you have to choose the best option."
Greedy Algorithm solves problems by making the best choice that seems best at a particular moment. Many optimization problems can be determined using a greedy algorithm. Some issues have no efficient solution, but a greedy algorithm may provide a solution that is close to optimal. A greedy algorithm works if a problem exhibits the following two properties:
Greedy Choice Property: A globally optimal solution can be reached by creating a locally optimal solution. In other words, an optimal solution can be obtained by creating "greedy" choices.
Optimal substructure: Optimal solutions contain optimal subsolutions. In other words, answers to subproblems of an optimal solution are optimal.
Example:
machine scheduling
Fractional Knapsack Problem
Minimum Spanning Tree
Huffman Code
Job Sequencing
Activity Selection Problem
