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이산 사건 시뮬레이션 (DES)×몬테카를로 시뮬레이션×
분야시뮬레이션의사결정
계열Process / pipelineMCDM
기원 연도1960s (formalized); modern computational form from 1970s onward1949
창시자Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)Metropolis, N., Ulam, S.
유형Stochastic process simulationRobustness wrapper — Monte Carlo uncertainty propagation
원전Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
별칭DES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
관련40
요약Discrete-Event Simulation (DES) is a computational modeling paradigm in which the state of a system changes only at a countable sequence of points in time — the events. Between events nothing changes, so the simulation clock jumps directly from one event to the next. Formalized through the foundational textbooks of Banks, Carson, Nelson and Nicol and of Law in the 1960s–2000s, DES has become the standard tool for analyzing queuing systems, healthcare patient flows, manufacturing lines, and logistics networks where entities move through resources over time.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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ScholarGate방법 비교: Discrete-Event Simulation · MONTE-CARLO-SIMULATION. 2026-06-17에 다음에서 검색함: https://scholargate.app/ko/compare