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Sammenlign metoder

Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.

Heltallsprogrammering×Dynamisk programmering×
FagfeltSimuleringOptimering
FamilieProcess / pipelineProcess / pipeline
Opprinnelsesår1958–19601957
OpphavspersonRalph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960)Richard Bellman
TypeMathematical optimizationExact combinatorial optimization via recursive decomposition
Opprinnelig kildeNemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. Wiley-Interscience, New York. ISBN: 9780471359432Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6
AliasMIP, Mixed-Integer Linear Programming, MILP, Integer ProgrammingDP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama
Relaterte63
SammendragMixed-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.Dynamic Programming (DP) is an exact optimization technique introduced by Richard Bellman in 1957 for solving multi-stage decision problems. It decomposes a complex problem into simpler, overlapping subproblems, solves each subproblem once, and stores the results to avoid redundant computation. Grounded in the Principle of Optimality, DP guarantees globally optimal solutions whenever the problem exhibits overlapping subproblems and optimal substructure.
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ScholarGateSammenlign metoder: Mixed-Integer Programming · Dynamic Programming. Hentet 2026-06-15 fra https://scholargate.app/no/compare