مقایسهٔ روشها
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| تحلیل سناریوی تصادفی× | برنامهریزی پویا تصادفی× | |
|---|---|---|
| حوزه | شبیهسازی | شبیهسازی |
| خانواده | Process / pipeline | Process / pipeline |
| سال پیدایش≠ | 1955–1980s | 1957 |
| پدیدآور≠ | Dantzig, G. B.; Birge, J. R.; and others in stochastic programming tradition | Bellman, R.; formalized for stochastic settings by Puterman, M. L. |
| نوع≠ | Probabilistic scenario enumeration and evaluation | Sequential optimization under uncertainty |
| منبع بنیادین≠ | Birge, J. R., Louveaux, F. (2011). Introduction to Stochastic Programming (2nd ed.). Springer. ISBN: 9781461402374 | Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780486428093 |
| نامهای دیگر | Probabilistic Scenario Analysis, SSA, Stochastic What-If Analysis, Monte Carlo Scenario Analysis | SDP, Markov Decision Process, MDP, Stochastic DP |
| مرتبط≠ | 4 | 6 |
| خلاصه≠ | Stochastic Scenario Analysis evaluates a system or decision across multiple explicitly defined scenarios, each assigned a probability of occurrence. Unlike deterministic scenario analysis, it propagates uncertainty through probability distributions and computes expected outcomes, variance, and risk metrics across the scenario space, giving decision-makers a structured view of what could happen and how likely each outcome is. | Stochastic Dynamic Programming (SDP) is a mathematical optimization framework for sequential decision problems where outcomes are partly random. It extends Bellman's principle of optimality to stochastic environments, representing problems as Markov Decision Processes (MDPs) and computing optimal policies by solving recursive value equations over states and time periods. |
| ScholarGateمجموعهداده ↗ |
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