Greedy Algorithms
Greedy algorithms are a class of algorithmic techniques that make locally optimal choices at each step with the hope of finding a globally optimal solution. They are used in optimization problems where a series of decisions must be made, and each decision is based on the current best option without reconsidering previous choices. While not always yielding the absolute best solution, greedy algorithms are often efficient and effective for problems with optimal substructure and the greedy-choice property.
Developers should learn greedy algorithms for solving optimization problems where speed and simplicity are prioritized, such as in scheduling, graph algorithms (e.g., Dijkstra's shortest path, Kruskal's minimum spanning tree), and data compression (e.g., Huffman coding). They are particularly useful in competitive programming, real-time systems, and resource allocation scenarios where approximate solutions are acceptable or guaranteed to be optimal for specific problem types.