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حوزهشبیه‌سازیشبیه‌سازی
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش19571955
پدیدآورBellman, R.; formalized for stochastic settings by Puterman, M. L.George B. Dantzig
نوعSequential optimization under uncertaintyStochastic optimization model
منبع بنیادینBellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780486428093Dantzig, G. B., & Madansky, A. (1961). On the solution of two-stage linear programs under uncertainty. Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, 1, 165–176. link ↗
نام‌های دیگرSDP, Markov Decision Process, MDP, Stochastic DPSLP, Stochastic LP, Linear Programming under Uncertainty, Two-Stage SLP
مرتبط65
خلاصهStochastic Dynamic Programming (SDP) is a mathematical optimization framework for sequential decision problems where outcomes are partly random. It extends Bellman's principle of optimality to stochastic environments, representing problems as Markov Decision Processes (MDPs) and computing optimal policies by solving recursive value equations over states and time periods.Stochastic Linear Programming (SLP) extends classical linear programming to settings where some model parameters — costs, demands, resource availability — are uncertain and modeled as random variables. By optimizing expected costs over a probability distribution of scenarios, SLP produces decisions that remain feasible and near-optimal across a range of possible futures rather than for a single assumed state of the world.
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ScholarGateمقایسهٔ روش‌ها: Stochastic Dynamic Programming · Stochastic Linear Programming. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare