Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Programmation dynamique× | Programmation linéaire× | |
|---|---|---|
| Domaine | Optimisation | Optimisation |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1957 | 1947 |
| Auteur d'origine≠ | Richard Bellman | George B. Dantzig |
| Type≠ | Exact combinatorial optimization via recursive decomposition | Mathematical programming / continuous optimization |
| Source fondatrice≠ | Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6 | Dantzig, G.B. (1963). Linear Programming and Extensions. Princeton University Press. ISBN: 9780691059136 |
| Alias≠ | DP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama | LP, linear optimization, Doğrusal Programlama (LP) |
| Apparentées≠ | 3 | 4 |
| Résumé≠ | Dynamic Programming (DP) is an exact optimization technique introduced by Richard Bellman in 1957 for solving multi-stage decision problems. It decomposes a complex problem into simpler, overlapping subproblems, solves each subproblem once, and stores the results to avoid redundant computation. Grounded in the Principle of Optimality, DP guarantees globally optimal solutions whenever the problem exhibits overlapping subproblems and optimal substructure. | Linear programming (LP), pioneered by George B. Dantzig in 1947, is a mathematical method for finding the best value of a linear objective function — such as minimum cost or maximum profit — subject to a set of linear inequality and equality constraints. It is the foundational technique in operations research and underlies production planning, resource allocation, logistics, diet problems, and countless other decision-making scenarios across engineering, economics, and the natural sciences. |
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