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Metoda Větve a mezí (Branch and Bound)×Dynamické programování×Celočíselné programování×
OborOptimalizaceOptimalizaceOptimalizace
RodinaProcess / pipelineProcess / pipelineProcess / pipeline
Rok vzniku196019571958
TvůrceAilsa Land & Alison DoigRichard BellmanRalph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960)
TypExact combinatorial optimization algorithmExact combinatorial optimization via recursive decompositionMathematical optimisation — exact combinatorial method
Původní zdrojLand, A. H., & Doig, A. G. (1960). An automatic method of solving discrete programming problems. Econometrica, 28(3), 497–520. DOI ↗Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669
Další názvyB&B, Land-Doig Algorithm, Implicit Enumeration, Dal ve SınırDP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik ProgramlamaIP, MIP, mixed-integer programming, mixed-integer linear programming
Příbuzné334
ShrnutíBranch 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.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.Integer programming (IP), also called mixed-integer programming (MIP) when only some variables are restricted to whole numbers, is a branch of mathematical optimisation in which some or all decision variables must take integer or binary values. Building on linear programming, it was formalised through Ralph Gomory's cutting-plane method (1958) and the Land-and-Doig branch-and-bound algorithm (1960), and it has since become the standard exact framework for scheduling, assignment, routing, and resource-allocation problems.
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ScholarGatePorovnat metody: Branch and Bound · Dynamic Programming · Integer Programming. Získáno 2026-06-15 z https://scholargate.app/cs/compare