Comparer des méthodes

	Programmation linéaire en nombres entiers multi-objectifs	Programmation dynamique multi-objectifs
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1980s–2000s	1957-1975
Auteur d'origine	Ehrgott, M.; Mavrotas, G. and others in multi-criteria optimization	Extension of Bellman (1957); formalized by multiple authors from 1970s onward
Type	Mathematical optimization	Exact optimization — recursive multi-objective decomposition
Source fondatrice	Ehrgott, M. (2005). Multicriteria Optimization (2nd ed.). Springer, Berlin. ISBN: 9783540213987	Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516
Alias	MO-MIP, Multi-criteria MIP, MOMIP, Multi-objective MILP	MODP, Multi-criteria dynamic programming, Vector dynamic programming, Pareto dynamic programming
Apparentées	5	5
Résumé	Multi-Objective Mixed-Integer Programming (MO-MIP) is an optimization framework that simultaneously optimizes two or more conflicting objective functions subject to linear or nonlinear constraints, where some decision variables are restricted to integer values and others are continuous. It is widely applied in engineering design, supply chain planning, resource allocation, and scheduling problems that require discrete choices alongside continuous quantities.	Multi-Objective Dynamic Programming (MODP) extends Bellman's classical dynamic programming to settings where a decision-maker must optimize several competing objectives simultaneously across a sequence of stages. Rather than a single optimal policy, it produces a Pareto-optimal set of policies — each representing a distinct trade-off profile — by propagating vector-valued value functions backward through the state space.