השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ניתוח תרחישים דטרמיניסטי× | ניתוח תרחישים סטוכסטי – הערכה הסתברותית מרובת תרחישים תחת אי-ודאות× | |
|---|---|---|
| תחום | סימולציה | סימולציה |
| משפחה | Process / pipeline | Process / pipeline |
| שנת המקור≠ | 1967 | 1955–1980s |
| הוגה השיטה≠ | Kahn, H., Wiener, A. J. (RAND Corporation / Hudson Institute) | Dantzig, G. B.; Birge, J. R.; and others in stochastic programming tradition |
| סוג≠ | Exploratory planning and decision-support framework | Probabilistic scenario enumeration and evaluation |
| מקור מכונן≠ | Kahn, H., Wiener, A. J. (1967). The Year 2000: A Framework for Speculation on the Next Thirty-Three Years. Macmillan, New York. ISBN: 9780025604407 | Birge, J. R., Louveaux, F. (2011). Introduction to Stochastic Programming (2nd ed.). Springer. ISBN: 9781461402374 |
| כינויים | DSA, Fixed-Input Scenario Analysis, Classical Scenario Analysis, Deterministic What-If Analysis | Probabilistic Scenario Analysis, SSA, Stochastic What-If Analysis, Monte Carlo Scenario Analysis |
| קשורות≠ | 5 | 4 |
| תקציר≠ | Deterministic 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. | 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. |
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