手法を比較

	離散事象シミュレーション（DES）	モンテカルロシミュレーション
分野	シミュレーション	意思決定
系統	Process / pipeline	MCDM
提唱年	1960s (formalized); modern computational form from 1970s onward	1949
提唱者	Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)	Metropolis, N., Ulam, S.
種類	Stochastic process simulation	Robustness wrapper — Monte Carlo uncertainty propagation
原典	Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
別名	DES, event-driven simulation, Ayrık Olay Simülasyonu (DES)	—
関連	4	0
概要	Discrete-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.