Optimal Substructure
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In computer science, a problem is said to have optimal substructure if an optimal solution can be constructed efficiently from optimal solutions to its subproblems. This property is used to determine the usefulness of dynamic programming and greedy algorithms in a problem. Typically, a greedy algorithm is used to solve a problem with optimal substructure if it can be proved by induction that this is optimal at each step (Cormen et al. pp. 381-2). Otherwise, providing ...
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In computer science, a problem is said to have optimal substructure if an optimal solution can be constructed efficiently from optimal solutions to its subproblems. This property is used to determine the usefulness of dynamic programming and greedy algorithms in a problem. Typically, a greedy algorithm is used to solve a problem with optimal substructure if it can be proved by induction that this is optimal at each step (Cormen et al. pp. 381-2). Otherwise, providing the problem exhibits overlapping subproblems as well, dynamic programming is used. If there are no appropriate greedy algorithms and the problem fails to exhibit overlapping subproblems, often a lengthy but straightforward search of the solution space is the best alternative.
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