A greedy algorithm solves problems by making the locally optimal choice at each step, aiming for a global optimum without revisiting decisions. It’s used in optimization tasks like scheduling, network routing, and Huffman coding. Software engineers, data scientists, and operations researchers benefit most, leveraging its speed and simplicity for large-scale problems where perfect solutions are computationally prohibitive.
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