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Deterministické celočíselné programování×Metoda Větve a mezí (Branch and Bound)×
OborSimulaceOptimalizace
RodinaProcess / pipelineProcess / pipeline
Rok vzniku19581960
TvůrceRalph E. GomoryAilsa Land & Alison Doig
TypExact combinatorial optimizationExact combinatorial optimization algorithm
Původní zdrojGomory, R. E. (1958). Outline of an algorithm for integer solutions to linear programs. Bulletin of the American Mathematical Society, 64(5), 275-278. DOI ↗Land, A. H., & Doig, A. G. (1960). An automatic method of solving discrete programming problems. Econometrica, 28(3), 497–520. DOI ↗
Další názvyDIP, Integer Programming, IP, Integer Linear ProgrammingB&B, Land-Doig Algorithm, Implicit Enumeration, Dal ve Sınır
Příbuzné53
ShrnutíDeterministic Integer Programming (DIP) is a mathematical optimization approach that finds the best solution to problems where some or all decision variables must take integer values, given fully known (deterministic) objective and constraint data. It is the classical, non-stochastic form of integer programming, foundational to operations research and combinatorial optimization since the late 1950s.Branch and Bound is a systematic exact algorithm for combinatorial and integer optimization problems, introduced by Ailsa Land and Alison Doig in 1960. It organizes the search space as a tree of subproblems, uses relaxation-derived upper bounds to prune branches that cannot improve the best known solution, and guarantees finding a globally optimal integer solution. It is the backbone of modern mixed-integer programming solvers used in operations research, logistics, scheduling, and engineering design.
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ScholarGatePorovnat metody: Deterministic Integer Programming · Branch and Bound. Získáno 2026-06-15 z https://scholargate.app/cs/compare