Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. Greedy algorithms are used for optimization problems.

- Activity Selection Problem
- Kruskal’s Minimum Spanning Tree Algorithm
- Huffman Coding
- Efficient Huffman Coding for Sorted Input
- Prim’s Minimum Spanning Tree Algorithm
- Prim’s MST for Adjacency List Representation
- Dijkstra’s Shortest Path Algorithm
- Dijkstra’s Algorithm for Adjacency List Representation
- Job Sequencing Problem
- Greedy Algorithm to find Minimum number of Coins
- K Centers Problem
- Minimum Number of Platforms Required for a Railway/Bus Station
- Connect n ropes with minimum cost
- Graph coloring
- Fractional Knapsack Problem
- Minimize Cash Flow among a given set of friends who have borrowed money from each other
- Find minimum time to finish all jobs with given constraints
- Find maximum sum possible equal to sum of three stacks
- Dail’s Algorithm
- Boruvka’s algorithm

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- Activity Selection Problem | Greedy Algo-1
- Huffman Coding | Greedy Algo-3
- Efficient Huffman Coding for Sorted Input | Greedy Algo-4
- Prim’s Minimum Spanning Tree (MST) | Greedy Algo-5
- Prim’s MST for Adjacency List Representation | Greedy Algo-6
- Dijkstra's shortest path algorithm | Greedy Algo-7
- Graph Coloring | Set 2 (Greedy Algorithm)
- Greedy Algorithm for Egyptian Fraction
- K Centers Problem | Set 1 (Greedy Approximate Algorithm)
- Set Cover Problem | Set 1 (Greedy Approximate Algorithm)