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| Ανάλυση Ευαισθησίας Πολλαπλών Στόχων× | Προσομοίωση Monte Carlo× | |
|---|---|---|
| Πεδίο≠ | Προσομοίωση | Λήψη Αποφάσεων |
| Οικογένεια≠ | Process / pipeline | MCDM |
| Έτος προέλευσης≠ | 1990s–2000s | 1949 |
| Δημιουργός≠ | Evolved from classical sensitivity analysis (Saltelli et al.) combined with multi-objective optimization (Pareto, 1896) | Metropolis, N., Ulam, S. |
| Τύπος≠ | Analytical technique — parametric sensitivity across multiple objectives | Robustness wrapper — Monte Carlo uncertainty propagation |
| Θεμελιώδης πηγή≠ | Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley, Chichester. ISBN: 9780470059975 | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Εναλλακτικές ονομασίες≠ | MOSA, Multi-criteria sensitivity analysis, Pareto sensitivity analysis, Multi-objective SA | — |
| Συναφείς≠ | 4 | 0 |
| Σύνοψη≠ | Multi-Objective Sensitivity Analysis (MOSA) examines how changes in model parameters, weights, or assumptions affect an entire set of competing objectives simultaneously. Rather than asking how a single output shifts, MOSA tracks changes in the Pareto front or trade-off surface, revealing which parameters most destabilize multi-objective solutions and where decision-maker choices are robust versus fragile. | 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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