Comparer des méthodes

	Simulation à événements discrets multi-objectifs	Simulation à événements discrets (DES)
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1990s–2000s	1960s (formalized); modern computational form from 1970s onward
Auteur d'origine	Various (DES: Tocher 1963; multi-objective integration: 1990s–2000s OR literature)	Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)
Type	Simulation-optimization hybrid	Stochastic process simulation
Source fondatrice	Kleijnen, J. P. C., & Gaury, E. (2003). Short-term robustness of production management systems: A case study. European Journal of Operational Research, 148(2), 452–465.	Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127
Alias	MO-DES, Multi-objective DES, Pareto-based discrete-event simulation, DES with multi-objective optimization	DES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
Apparentées	5	4
Résumé	Multi-Objective Discrete-Event Simulation (MO-DES) couples a discrete-event simulation engine with multi-objective optimization to explore trade-offs among two or more conflicting performance measures — such as throughput, cost, and waiting time — across stochastic, time-ordered process models. It is widely applied in manufacturing, logistics, healthcare, and service system design.	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.