Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Детерминированное смешанно-целочисленное программирование× | Детерминированное линейное программирование× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1958–1960 | 1947 |
| Автор метода≠ | Gomory, R. E.; Dantzig, G. B.; Land, A. H.; Doig, A. G. | George B. Dantzig |
| Тип≠ | Mathematical programming / combinatorial optimization | Deterministic mathematical optimization |
| Основополагающий источник≠ | Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. John Wiley & Sons, New York. ISBN: 9780471359432 | Dantzig, G. B. (1963). Linear Programming and Extensions. Princeton University Press, Princeton, NJ. ISBN: 9780691059136 |
| Другие названия | Deterministic MIP, Deterministic MILP/MIQP, Classical Mixed-Integer Programming, Deterministic MIP Optimization | Classical LP, Deterministic LP, DLP, Linear Optimization |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Deterministic Mixed-Integer Programming (MIP) is a mathematical optimization framework that finds the provably optimal solution to problems involving both continuous and integer decision variables under fully known, fixed coefficients and constraints. It is the foundational workhorse of operations research when all data are treated as certain. | Deterministic Linear Programming (DLP) is the classical form of linear programming in which all objective function coefficients, constraint coefficients, and right-hand-side values are known with certainty. It finds the optimal allocation of resources to maximize or minimize a linear objective subject to linear constraints, providing an exact, reproducible solution under fixed, certain data. |
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