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برنامه‌ریزی پویا قطعی×مدل مارکوف×
حوزهشبیه‌سازیشبیه‌سازی
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش19571906
پدیدآورRichard E. BellmanAndrei Markov
نوعExact sequential optimization algorithmProbabilistic state-transition model
منبع بنیادینBellman, R. E. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963
نام‌های دیگرDDP, Deterministic DP, Classical Dynamic Programming, Bellman Dynamic ProgrammingMarkov Chain, Discrete-Time Markov Chain, DTMC, Markov Process
مرتبط65
خلاصهDeterministic Dynamic Programming (DDP) is a mathematical optimization technique that decomposes a multi-stage decision problem into a sequence of simpler subproblems, solving them exactly when all system parameters — transition functions, costs, and rewards — are known with certainty. It guarantees a globally optimal policy via Bellman's principle of optimality.A Markov Model represents a system as a finite set of states and specifies the probability of moving from one state to another at each time step. By capturing only the current state — not the full history — it enables tractable analysis of complex dynamic processes across health economics, engineering reliability, operations research, and social-science modeling.
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ScholarGateمقایسهٔ روش‌ها: Deterministic Dynamic Programming · Markov Model. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare