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System Dynamics×Diskrétní simulace událostí (DES)×Simulace Monte Carlo×
OborSimulaceSimulaceRozhodování
RodinaProcess / pipelineProcess / pipelineMCDM
Rok vzniku19611960s (formalized); modern computational form from 1970s onward1949
TvůrceJay W. ForresterBanks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)Metropolis, N., Ulam, S.
TypContinuous simulation / feedback modellingStochastic process simulationRobustness wrapper — Monte Carlo uncertainty propagation
Původní zdrojSterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159Banks, 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 ↗
Další názvystock-flow modelling, Sistem Dinamiği (Stock-Flow Modelleme), SD modelling, feedback simulationDES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
Příbuzné340
ShrnutíSystem dynamics is a continuous simulation method, developed by Jay W. Forrester at MIT in 1961, that represents a complex system through stocks (accumulations), flows (rates of change), and feedback loops. By expressing these relationships as coupled ordinary differential equations, it reproduces how policies, delays, and nonlinear feedbacks drive system behaviour over time — making it a cornerstone tool in policy analysis, organisational modelling, and sustainability research.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.
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ScholarGatePorovnat metody: System Dynamics · Discrete-Event Simulation · MONTE-CARLO-SIMULATION. Získáno 2026-06-17 z https://scholargate.app/cs/compare