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Comparar métodos

Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Programação Dinâmica×Programação Inteira×
ÁreaOtimizaçãoOtimização
FamíliaProcess / pipelineProcess / pipeline
Ano de origem19571958
Autor originalRichard BellmanRalph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960)
TipoExact combinatorial optimization via recursive decompositionMathematical optimisation — exact combinatorial method
Fonte seminalBellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669
Outros nomesDP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik ProgramlamaIP, MIP, mixed-integer programming, mixed-integer linear programming
Relacionados34
ResumoDynamic 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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ScholarGateComparar métodos: Dynamic Programming · Integer Programming. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare