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Динамическое программирование×Целочисленное программирование×
ОбластьОптимизацияОптимизация
СемействоProcess / pipelineProcess / pipeline
Год появления19571958
Автор методаRichard BellmanRalph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960)
ТипExact combinatorial optimization via recursive decompositionMathematical optimisation — exact combinatorial method
Основополагающий источникBellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669
Другие названияDP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik ProgramlamaIP, MIP, mixed-integer programming, mixed-integer linear programming
Связанные34
СводкаDynamic 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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ScholarGateСравнение методов: Dynamic Programming · Integer Programming. Получено 2026-06-15 из https://scholargate.app/ru/compare