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Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Simulação Robusta de Eventos Discretos×Simulação de Eventos Discretos (DES)×
ÁreaSimulaçãoSimulação
FamíliaProcess / pipelineProcess / pipeline
Ano de origem1990s–2000s1960s (formalized); modern computational form from 1970s onward
Autor originalBanks, Carson, Nelson, Nicol (canonical DES); robust extensions: operations research communityBanks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)
TipoSimulation with robustness analysisStochastic process simulation
Fonte seminalBanks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127
Outros nomesRobust DES, Uncertainty-Aware DES, Robust DEVS, Resilient Discrete-Event SimulationDES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
Relacionados64
ResumoRobust Discrete-Event Simulation (Robust DES) is a simulation methodology that extends classical discrete-event simulation by explicitly incorporating uncertainty in model parameters — such as interarrival times, service durations, and resource capacities — and evaluating system performance across worst-case or distributional uncertainty sets rather than point estimates alone. It is widely applied in manufacturing, healthcare, logistics, and supply chain systems where parameter misspecification or real-world variability can lead to misleading simulation conclusions.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.
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ScholarGateComparar métodos: Robust Discrete-Event Simulation · Discrete-Event Simulation. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare