Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Programmation en nombres entiers déterministe× | Programmation linéaire× | |
|---|---|---|
| Domaine≠ | Simulation | Optimisation |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1958 | 1947 |
| Auteur d'origine≠ | Ralph E. Gomory | George B. Dantzig |
| Type≠ | Exact combinatorial optimization | Mathematical programming / continuous optimization |
| Source fondatrice≠ | Gomory, R. E. (1958). Outline of an algorithm for integer solutions to linear programs. Bulletin of the American Mathematical Society, 64(5), 275-278. DOI ↗ | Dantzig, G.B. (1963). Linear Programming and Extensions. Princeton University Press. ISBN: 9780691059136 |
| Alias≠ | DIP, Integer Programming, IP, Integer Linear Programming | LP, linear optimization, Doğrusal Programlama (LP) |
| Apparentées≠ | 5 | 4 |
| Résumé≠ | Deterministic Integer Programming (DIP) is a mathematical optimization approach that finds the best solution to problems where some or all decision variables must take integer values, given fully known (deterministic) objective and constraint data. It is the classical, non-stochastic form of integer programming, foundational to operations research and combinatorial optimization since the late 1950s. | 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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