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Dinâmica de Sistemas×Simulação de Eventos Discretos (DES)×Simulação de Monte Carlo×
ÁreaSimulaçãoSimulaçãoTomada de decisão
FamíliaProcess / pipelineProcess / pipelineMCDM
Ano de origem19611960s (formalized); modern computational form from 1970s onward1949
Autor originalJay W. ForresterBanks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)Metropolis, N., Ulam, S.
TipoContinuous simulation / feedback modellingStochastic process simulationRobustness wrapper — Monte Carlo uncertainty propagation
Fonte seminalSterman, 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 ↗
Outros nomesstock-flow modelling, Sistem Dinamiği (Stock-Flow Modelleme), SD modelling, feedback simulationDES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
Relacionados340
ResumoSystem 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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ScholarGateComparar métodos: System Dynamics · Discrete-Event Simulation · MONTE-CARLO-SIMULATION. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare