Comparer des méthodes

	Dynamique des systèmes basée sur les agents	Dynamique des Systèmes Multi-Objectifs
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	2000s	1961 (SD); multi-objective extensions from 1990s onward
Auteur d'origine	Borshchev, A. & Filippov, A. (hybrid formalization); Sterman, J. D. (system dynamics foundation)	Forrester, J. W. (System Dynamics); multi-objective extension by various authors
Type	Hybrid simulation model	Simulation / optimization hybrid
Source fondatrice	Borshchev, A., & Filippov, A. (2004). From system dynamics and discrete event to practical agent based modeling: Reasons, techniques, tools. In Proceedings of the 22nd International Conference of the System Dynamics Society. Oxford, UK.	Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill. ISBN: 978-0-07-231135-8
Alias	AB-SD, Hybrid ABM-SD, Agent-based SD, Multi-level hybrid simulation	MOSD, Multi-criteria SD, Multi-objective SD modeling, System dynamics with multiple objectives
Apparentées	5	4
Résumé	Agent-based system dynamics (AB-SD) is a hybrid simulation paradigm that couples agent-based modeling (ABM) at the micro level with system dynamics (SD) stock-and-flow structures at the macro level. This allows researchers to capture emergent individual behavior and feedback-driven aggregate dynamics within a single coherent model, making it especially valuable for complex socio-economic and epidemiological systems.	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.