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

Programação Inteira×Programação Dinâmica×
ÁreaOtimizaçãoOtimização
FamíliaProcess / pipelineProcess / pipeline
Ano de origem19581957
Autor originalRalph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960)Richard Bellman
TipoMathematical optimisation — exact combinatorial methodExact combinatorial optimization via recursive decomposition
Fonte seminalWolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6
Outros nomesIP, MIP, mixed-integer programming, mixed-integer linear programmingDP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama
Relacionados43
ResumoInteger 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.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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ScholarGateComparar métodos: Integer Programming · Dynamic Programming. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare