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분야시뮬레이션의사결정
계열Process / pipelineMCDM
기원 연도1960s (formalised in literature through the 1980s–2000s)1949
창시자Kelton, Law & Sadowski (formalised methodology); SIMSCRIPT (Markowitz et al., 1963) and GPSS (Gordon, 1961) were pioneering toolsMetropolis, N., Ulam, S.
유형Stochastic process simulationRobustness wrapper — Monte Carlo uncertainty propagation
원전Kelton, W.D., Sadowski, R.P. & Zupick, N.B. (2014). Simulation with Arena (6th ed.). McGraw-Hill. ISBN: 978-0073401317Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
별칭DES, discrete event simulation, Kesikli Sistem Simülasyonu (Arena / AnyLogic tarzı)
관련40
요약Discrete-event system simulation (DES) is a computational modelling technique in which the state of a system changes only at discrete points in time — called events — such as a customer arriving, a machine starting, or a job completing. Formalised through foundational texts by Kelton, Sadowski, and Zupick (2014) and Law (2015), DES represents processes as networks of resources, queues, and activities, allowing analysts to test capacity and policy changes on a virtual model before touching the real system.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 System Simulation · MONTE-CARLO-SIMULATION. 2026-06-17에 다음에서 검색함: https://scholargate.app/ko/compare