So sánh phương pháp

	Lập trình động theo kịch bản chính sách	Mô hình Markov
Lĩnh vực	Mô phỏng	Mô phỏng
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1957	1906
Người khởi xướng	Bellman, Richard E.	Andrei Markov
Loại	Sequential optimization with scenario branching	Probabilistic state-transition model
Công trình gốc	Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516	Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963
Tên gọi khác	PSDP, Policy-Scenario DP, Scenario-Based Dynamic Programming, Policy DP	Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process
Liên quan	5	5
Tóm tắt	Policy Scenario Dynamic Programming (PSDP) applies Bellman's recursive optimization framework to a set of pre-specified policy scenarios, enabling decision-makers to compare staged, sequential decisions under distinct future conditions. It decomposes a complex, multi-period policy choice into tractable sub-problems solved backward through time, yielding optimal action sequences for each scenario and a structured basis for scenario comparison.	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.