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Pengaturcaraan Dinamik Deterministik×Pengaturcaraan Integer Campuran×
BidangSimulasiSimulasi
KeluargaProcess / pipelineProcess / pipeline
Tahun asal19571958–1960
PengasasRichard E. BellmanRalph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960)
JenisExact sequential optimization algorithmMathematical optimization
Sumber perintisBellman, R. E. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. Wiley-Interscience, New York. ISBN: 9780471359432
AliasDDP, Deterministic DP, Classical Dynamic Programming, Bellman Dynamic ProgrammingMIP, Mixed-Integer Linear Programming, MILP, Integer Programming
Berkaitan66
RingkasanDeterministic 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.Mixed-Integer Programming (MIP) is a mathematical optimization framework in which some decision variables must take integer values while others may be continuous. It generalizes linear programming and is widely used in operations research, logistics, scheduling, resource allocation, and engineering design, where indivisibility constraints — such as yes/no decisions or whole-unit quantities — arise naturally.
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ScholarGateBandingkan kaedah: Deterministic Dynamic Programming · Mixed-Integer Programming. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare