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Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Programování se smíšenými celočíselnými proměnnými×Dynamické programování×
OborSimulaceOptimalizace
RodinaProcess / pipelineProcess / pipeline
Rok vzniku1958–19601957
TvůrceRalph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960)Richard Bellman
TypMathematical optimizationExact combinatorial optimization via recursive decomposition
Původní zdrojNemhauser, 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
Další názvyMIP, Mixed-Integer Linear Programming, MILP, Integer ProgrammingDP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama
Příbuzné63
ShrnutíMixed-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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ScholarGatePorovnat metody: Mixed-Integer Programming · Dynamic Programming. Získáno 2026-06-15 z https://scholargate.app/cs/compare