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제약 프로그래밍×동적 계획법×정수 계획법(IP) 및 혼합 정수 계획법(MIP)×
분야최적화최적화최적화
계열Process / pipelineProcess / pipelineProcess / pipeline
기원 연도200619571958
창시자Rossi, van Beek & WalshRichard BellmanRalph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960)
유형Declarative combinatorial optimizationExact combinatorial optimization via recursive decompositionMathematical optimisation — exact combinatorial method
원전Rossi, F., van Beek, P., & Walsh, T. (Eds.). (2006). Handbook of Constraint Programming. Elsevier. ISBN: 978-0-444-52726-4Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669
별칭Constraint Satisfaction Programming, Constraint-Based Optimization, Kısıt Programlama, CSP OptimizationDP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik ProgramlamaIP, MIP, mixed-integer programming, mixed-integer linear programming
관련334
요약Constraint Programming (CP) is a declarative optimization paradigm in which a problem is formulated as a set of variables, finite domains, and constraints, and a solver systematically searches for assignments that satisfy all constraints. Formalized comprehensively by Rossi, van Beek, and Walsh in their 2006 Handbook of Constraint Programming, CP unifies propagation-based pruning with intelligent backtracking search to tackle combinatorial problems across scheduling, planning, and configuration domains.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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ScholarGate방법 비교: Constraint Programming · Dynamic Programming · Integer Programming. 2026-06-15에 다음에서 검색함: https://scholargate.app/ko/compare