Comparer des méthodes

	Simulation de files d'attente 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	Operations research community (Banks, Deb, and related authors)	Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)
Type	Simulation-based multi-objective optimization	Stochastic process simulation
Source fondatrice	Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Pearson Prentice Hall. ISBN: 9780136062127	Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127
Alias	MOQS, Multi-criteria Queueing Simulation, Multi-objective Queue Optimization, Pareto Queueing Simulation	DES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
Apparentées	4	4
Résumé	Multi-objective queueing simulation combines discrete-event queueing models with multi-objective optimization to simultaneously evaluate and optimize conflicting performance metrics — such as average wait time, server utilization, throughput, and service cost — across a simulated queuing system. It produces a Pareto front of non-dominated solutions rather than a single optimal point, enabling decision-makers to understand trade-offs explicitly.	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.