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| Lập trình động× | Lập trình ràng buộc× | Lập trình nguyên (Integer Programming× | |
|---|---|---|---|
| Lĩnh vực | Tối ưu hóa | Tối ưu hóa | Tối ưu hóa |
| Họ | Process / pipeline | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1957 | 2006 | 1958 |
| Người khởi xướng≠ | Richard Bellman | Rossi, van Beek & Walsh | Ralph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960) |
| Loại≠ | Exact combinatorial optimization via recursive decomposition | Declarative combinatorial optimization | Mathematical optimisation — exact combinatorial method |
| Công trình gốc≠ | Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6 | Rossi, F., van Beek, P., & Walsh, T. (Eds.). (2006). Handbook of Constraint Programming. Elsevier. ISBN: 978-0-444-52726-4 | Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669 |
| Tên gọi khác≠ | DP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama | Constraint Satisfaction Programming, Constraint-Based Optimization, Kısıt Programlama, CSP Optimization | IP, MIP, mixed-integer programming, mixed-integer linear programming |
| Liên quan≠ | 3 | 3 | 4 |
| Tóm tắt≠ | 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. | Constraint 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. | 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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