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Pengaturcaraan Dinamik Multi-Objektif×Pengaturcaraan Dinamik Stokastik×
BidangSimulasiSimulasi
KeluargaProcess / pipelineProcess / pipeline
Tahun asal1957-19751957
PengasasExtension of Bellman (1957); formalized by multiple authors from 1970s onwardBellman, R.; formalized for stochastic settings by Puterman, M. L.
JenisExact optimization — recursive multi-objective decompositionSequential optimization under uncertainty
Sumber perintisBellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780486428093
AliasMODP, Multi-criteria dynamic programming, Vector dynamic programming, Pareto dynamic programmingSDP, Markov Decision Process, MDP, Stochastic DP
Berkaitan56
RingkasanMulti-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.Stochastic 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.
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ScholarGateBandingkan kaedah: Multi-objective dynamic programming · Stochastic Dynamic Programming. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare