Comparar métodos

	Programação Dinâmica Multi-Objetivo	Programação Linear Multi-Objetivo (PLMO)
Área	Simulação	Simulação
Família	Process / pipeline	Process / pipeline
Ano de origem	1957-1975	1955–1986
Autor original	Extension of Bellman (1957); formalized by multiple authors from 1970s onward	Steuer, R. E.; Charnes, A.; Cooper, W. W.
Tipo	Exact optimization — recursive multi-objective decomposition	Mathematical optimization / vector optimization
Fonte seminal	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
Outros nomes	MODP, Multi-criteria dynamic programming, Vector dynamic programming, Pareto dynamic programming	MOLP, Vector Linear Programming, Multi-criteria LP, Linear Vector Optimization
Relacionados	5	3
Resumo	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.