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شبیه‌سازی رویداد-گسسته سناریوی خط‌مشی×شبیه‌سازی مونت کارلو×
حوزهشبیه‌سازیتصمیم‌گیری
خانوادهProcess / pipelineMCDM
سال پیدایش1960s–1990s1949
پدیدآورTocher, K. D. and Gordon, G. (early DES); policy scenario extension emerged through operations research and health policy modeling communitiesMetropolis, N., Ulam, S.
نوعSimulation-based policy evaluationRobustness wrapper — Monte Carlo uncertainty propagation
منبع بنیادینLaw, A. M. (2015). Simulation Modeling and Analysis (5th ed.). McGraw-Hill Education. ISBN: 9780073401324Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
نام‌های دیگرPolicy DES, Scenario-based DES, Policy simulation DES, DES policy analysis
مرتبط50
خلاصهPolicy Scenario Discrete-Event Simulation combines the event-by-event fidelity of Discrete-Event Simulation with systematic policy scenario analysis to evaluate how different interventions, regulations, or resource allocations change system performance. By running multiple well-defined policy scenarios through the same DES model, analysts can compare outcomes — throughput, waiting times, costs — across alternatives before real-world implementation.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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ScholarGateمقایسهٔ روش‌ها: Policy Scenario Discrete-Event Simulation · MONTE-CARLO-SIMULATION. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare