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برنامه‌ریزی پویا چندهدفه×الگوریتم ژنتیک چندهدفه (MOGA)×
حوزهشبیه‌سازیشبیه‌سازی
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش1957-19751984
پدیدآورExtension of Bellman (1957); formalized by multiple authors from 1970s onwardSchaffer, J. D. (early MOGA); Goldberg, D. E. (GA foundations)
نوعExact optimization — recursive multi-objective decompositionPopulation-based evolutionary optimizer
منبع بنیادینBellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Addison-Wesley. ISBN: 9780201157673
نام‌های دیگرMODP, Multi-criteria dynamic programming, Vector dynamic programming, Pareto dynamic programmingMOGA, Multi-objective GA, Evolutionary multi-objective optimization, EMO
مرتبط54
خلاصهMulti-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.
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ScholarGateمقایسهٔ روش‌ها: Multi-objective dynamic programming · Multi-objective genetic algorithm. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare