Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Детерминированное линейное программирование× | Многокритериальное линейное программирование (МКЛП)× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1947 | 1955–1986 |
| Автор метода≠ | George B. Dantzig | Steuer, R. E.; Charnes, A.; Cooper, W. W. |
| Тип≠ | Deterministic mathematical optimization | Mathematical optimization / vector optimization |
| Основополагающий источник≠ | Dantzig, G. B. (1963). Linear Programming and Extensions. Princeton University Press, Princeton, NJ. ISBN: 9780691059136 | Steuer, R. E. (1986). Multiple Criteria Optimization: Theory, Computation, and Application. John Wiley & Sons, New York. ISBN: 9780471888468 |
| Другие названия | Classical LP, Deterministic LP, DLP, Linear Optimization | MOLP, Vector Linear Programming, Multi-criteria LP, Linear Vector Optimization |
| Связанные≠ | 5 | 3 |
| Сводка≠ | 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. | Multi-Objective Linear Programming (MOLP) extends classical linear programming to handle several conflicting linear objective functions simultaneously over a feasible region defined by linear constraints. Instead of a single optimal solution, MOLP produces a Pareto-efficient frontier from which a decision-maker selects a preferred trade-off. It is foundational to operations research and management science for resource allocation, planning, and design problems with competing goals. |
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