Greedy Algorithms

Greedy algorithms make locally optimal choices at each step, hoping to find a global optimum. Master the principles and applications of greedy algorithms.

Learning Map

Greedy algorithm concepts organized from fundamentals to applications.

Prerequisites

• Time & Space Complexity Analysis
• Basic Data Structures
• Arrays & Strings

What's in scope

• Greedy Fundamentals: Greedy choice property, optimal substructure, proof techniques, and when to use greedy
• Classic Greedy Problems: Activity selection, fractional knapsack, Huffman coding, minimum spanning tree, and shortest path
• Advanced Greedy: Interval scheduling, set cover, job scheduling, resource allocation, and optimization problems

How to use this section

• Start with Greedy Fundamentals to understand core concepts
• Practice Classic Greedy Problems for essential algorithms
• Explore Advanced Greedy for complex applications

📄️ Greedy Fundamentals

Master greedy algorithm principles including greedy choice property, optimal substructure, proof techniques, and when greedy applies.

📄️ Classic Greedy Problems

Master the most important greedy algorithm problems: fractional knapsack, Huffman coding, job scheduling, and interval scheduling maximization

📄️ Advanced Greedy

Master advanced greedy techniques including greedy with sorting, priority queue applications, task scheduling, and when greedy fails.