Speed Over Hindsight: When Greedy Choices Lead to Global Solutions

Greedy algorithms offer developers a high-performance approach to optimization by making locally optimal choices at each step, delivering superior speed and simplicity compared to dynamic programming. However, their success depends critically on problem structure—they fail on arbitrary coin denominations but excel when local choices guarantee global optimality. Understanding this trade-off between speed and correctness is essential for effective algorithm selection.