Comparer des méthodes

	Programmation par objectifs basée sur les agents	Programmation par objectifs multi-objectifs
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1990s-2000s (hybrid integration)	1961
Auteur d'origine	Charnes, Cooper (GP); Schelling, Holland (ABM foundations)	Charnes, A. and Cooper, W. W.
Type	Hybrid simulation-optimization	Mathematical programming / multi-criteria optimization
Source fondatrice	Charnes, A., Cooper, W. W., & Ferguson, R. O. (1955). Optimal estimation of executive compensation by linear programming. Management Science, 1(2), 138-151.	Charnes, A., Cooper, W. W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York. ISBN: 978-0471148258
Alias	ABGP, Agent-Based GP, ABM-GP, Agent-Driven Goal Programming	MOGP, Multi-goal programming, Vector goal programming, Multi-criteria goal programming
Apparentées	5	4
Résumé	Agent-Based Goal Programming (ABGP) integrates agent-based simulation with goal programming optimization to model systems where multiple autonomous decision-makers pursue competing, prioritized goals. It enables researchers to study how decentralized, adaptive behavior at the agent level leads to system-level outcomes measured against predefined targets, capturing both emergence and multi-criteria satisfaction simultaneously.	Multi-Objective Goal Programming (MOGP) is a mathematical programming technique that simultaneously pursues several aspirational targets by minimizing weighted deviations from each goal. Rooted in Charnes and Cooper's original goal programming framework (1961), MOGP extends it to handle multiple competing objectives, making it indispensable in operations research, supply chain design, resource allocation, and policy analysis where decision-makers must satisfy — or come close to — multiple conflicting requirements at once.