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Determinētiskā scenāriju analīze×Monte Carlo simulācija×
NozareSimulācijaLēmumu pieņemšana
SaimeProcess / pipelineMCDM
Izcelsmes gads19671949
AutorsKahn, H., Wiener, A. J. (RAND Corporation / Hudson Institute)Metropolis, N., Ulam, S.
TipsExploratory planning and decision-support frameworkRobustness wrapper — Monte Carlo uncertainty propagation
PirmavotsKahn, H., Wiener, A. J. (1967). The Year 2000: A Framework for Speculation on the Next Thirty-Three Years. Macmillan, New York. ISBN: 9780025604407Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Citi nosaukumiDSA, Fixed-Input Scenario Analysis, Classical Scenario Analysis, Deterministic What-If Analysis
Saistītās50
KopsavilkumsDeterministic Scenario Analysis (DSA) is a structured planning method in which analysts construct a finite set of internally consistent future scenarios, each defined by fixed, precisely specified parameter values rather than probability distributions. By running a model or calculation under each scenario's fixed inputs, decision-makers can map how outcomes diverge across plausible futures and stress-test strategies without requiring full probabilistic characterization of uncertainty.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateSalīdzināt metodes: Deterministic Scenario Analysis · MONTE-CARLO-SIMULATION. Izgūts 2026-06-17 no https://scholargate.app/lv/compare