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결정론적 동적 계획법×Mixed-Integer Programming×
분야시뮬레이션시뮬레이션
계열Process / pipelineProcess / pipeline
기원 연도19571958–1960
창시자Richard E. BellmanRalph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960)
유형Exact sequential optimization algorithmMathematical optimization
원전Bellman, 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
별칭DDP, Deterministic DP, Classical Dynamic Programming, Bellman Dynamic ProgrammingMIP, Mixed-Integer Linear Programming, MILP, Integer Programming
관련66
요약Deterministic 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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