手法を比較

	Multi-Objective Dynamic Programming	多目的遺伝的アルゴリズム（MOGA）
分野	シミュレーション	シミュレーション
系統	Process / pipeline	Process / pipeline
提唱年	1957-1975	1984
提唱者	Extension of Bellman (1957); formalized by multiple authors from 1970s onward	Schaffer, J. D. (early MOGA); Goldberg, D. E. (GA foundations)
種類	Exact optimization — recursive multi-objective decomposition	Population-based evolutionary optimizer
原典	Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516	Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Addison-Wesley. ISBN: 9780201157673
別名	MODP, Multi-criteria dynamic programming, Vector dynamic programming, Pareto dynamic programming	MOGA, Multi-objective GA, Evolutionary multi-objective optimization, EMO
関連	5	4
概要	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.	A Multi-Objective Genetic Algorithm (MOGA) is an evolutionary computation method that evolves a population of candidate solutions toward a Pareto-optimal front, simultaneously optimizing two or more conflicting objective functions. It avoids collapsing trade-offs into a single score, instead producing a set of non-dominated solutions for the decision-maker to choose among.