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| Constraint Programming× | Målprogrammering× | Linjärprogrammering× | |
|---|---|---|---|
| Ämnesområde≠ | Optimering | Beslutsfattande | Optimering |
| Familj≠ | Process / pipeline | MCDM | Process / pipeline |
| Ursprungsår≠ | 2006 | 1955 | 1947 |
| Upphovsperson≠ | Rossi, van Beek & Walsh | Charnes, A., Cooper, W. W. | George B. Dantzig |
| Typ≠ | Declarative combinatorial optimization | Multi-objective optimisation — weighted/lexicographic goal deviation minimisation | Mathematical programming / continuous optimization |
| Ursprungskälla≠ | Rossi, F., van Beek, P., & Walsh, T. (Eds.). (2006). Handbook of Constraint Programming. Elsevier. ISBN: 978-0-444-52726-4 | Charnes, A., Cooper, W. W. (1955). Optimal estimation of executive compensation by linear programming. Management Science DOI ↗ | Dantzig, G.B. (1963). Linear Programming and Extensions. Princeton University Press. ISBN: 9780691059136 |
| Alias≠ | Constraint Satisfaction Programming, Constraint-Based Optimization, Kısıt Programlama, CSP Optimization | — | LP, linear optimization, Doğrusal Programlama (LP) |
| Närliggande≠ | 3 | 8 | 4 |
| Sammanfattning≠ | 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. | GOAL-PROGRAMMING (Goal Programming — Minimise deviations from multiple aspiration levels) is a ranking multi-criteria decision-making (MCDM) method introduced by Charnes, A., Cooper, W. W. in 1955. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | Linear programming (LP), pioneered by George B. Dantzig in 1947, is a mathematical method for finding the best value of a linear objective function — such as minimum cost or maximum profit — subject to a set of linear inequality and equality constraints. It is the foundational technique in operations research and underlies production planning, resource allocation, logistics, diet problems, and countless other decision-making scenarios across engineering, economics, and the natural sciences. |
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