Comparer des méthodes

	Programmation dynamique multi-objectifs	Programmation Linéaire Multi-Objectif (PLMO)
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1957-1975	1955–1986
Auteur d'origine	Extension of Bellman (1957); formalized by multiple authors from 1970s onward	Steuer, R. E.; Charnes, A.; Cooper, W. W.
Type	Exact optimization — recursive multi-objective decomposition	Mathematical optimization / vector optimization
Source fondatrice	Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516	Steuer, R. E. (1986). Multiple Criteria Optimization: Theory, Computation, and Application. John Wiley & Sons, New York. ISBN: 9780471888468
Alias	MODP, Multi-criteria dynamic programming, Vector dynamic programming, Pareto dynamic programming	MOLP, Vector Linear Programming, Multi-criteria LP, Linear Vector Optimization
Apparentées	5	3
Résumé	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.	Multi-Objective Linear Programming (MOLP) extends classical linear programming to handle several conflicting linear objective functions simultaneously over a feasible region defined by linear constraints. Instead of a single optimal solution, MOLP produces a Pareto-efficient frontier from which a decision-maker selects a preferred trade-off. It is foundational to operations research and management science for resource allocation, planning, and design problems with competing goals.