Comparer des méthodes

	Dynamique des Systèmes Multi-Objectifs	Dynamique stochastique des systèmes
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1961 (SD); multi-objective extensions from 1990s onward	1980s–2000s
Auteur d'origine	Forrester, J. W. (System Dynamics); multi-objective extension by various authors	Jay W. Forrester (base SD); stochastic extensions developed through 1980s–2000s by multiple researchers
Type	Simulation / optimization hybrid	Continuous stochastic simulation
Source fondatrice	Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill. ISBN: 978-0-07-231135-8	Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159
Alias	MOSD, Multi-criteria SD, Multi-objective SD modeling, System dynamics with multiple objectives	SSD, stochastic stock-flow modelling, probabilistic system dynamics, random system dynamics
Apparentées	4	5
Résumé	Multi-Objective System Dynamics (MOSD) couples the feedback-loop simulation power of System Dynamics with explicit multi-criteria optimization, enabling analysts to explore how a dynamic system can simultaneously satisfy competing policy goals — such as cost minimization, environmental sustainability, and social equity — over time.	Stochastic System Dynamics (SSD) extends conventional system dynamics by replacing fixed parameter values and deterministic flow equations with probability distributions and random draws. Running many replications of the stock-flow model yields probabilistic trajectories — confidence bands rather than single lines — enabling rigorous uncertainty quantification and risk analysis in complex feedback systems such as epidemic models, supply chains, and energy policy scenarios.