Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Детерминированное динамическое программирование× | Многокритериальная динамическая программа× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1957 | 1957-1975 |
| Автор метода≠ | Richard E. Bellman | Extension of Bellman (1957); formalized by multiple authors from 1970s onward |
| Тип≠ | Exact sequential optimization algorithm | Exact optimization — recursive multi-objective decomposition |
| Основополагающий источник≠ | Bellman, R. E. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516 | Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516 |
| Другие названия | DDP, Deterministic DP, Classical Dynamic Programming, Bellman Dynamic Programming | MODP, Multi-criteria dynamic programming, Vector dynamic programming, Pareto dynamic programming |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Deterministic Dynamic Programming (DDP) is a mathematical optimization technique that decomposes a multi-stage decision problem into a sequence of simpler subproblems, solving them exactly when all system parameters — transition functions, costs, and rewards — are known with certainty. It guarantees a globally optimal policy via Bellman's principle of optimality. | Multi-Objective Dynamic Programming (MODP) extends Bellman's classical dynamic programming to settings where a decision-maker must optimize several competing objectives simultaneously across a sequence of stages. Rather than a single optimal policy, it produces a Pareto-optimal set of policies — each representing a distinct trade-off profile — by propagating vector-valued value functions backward through the state space. |
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