When is dynamic programming preferable over greedy algorithms?
- Problems with constant time complexity
- Problems with large input sizes
- Problems with no overlapping subproblems
- Problems with optimal substructure
Dynamic programming is preferable over greedy algorithms when the problem exhibits optimal substructure, meaning the solution to the overall problem can be constructed from solutions to its subproblems. Greedy algorithms, on the other hand, make locally optimal choices at each step, which may not always lead to a globally optimal solution.
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