Methoden vergleichen

	Constraint-Programmierung	Dynamische Programmierung	Zielprogrammierung	Lineare Programmierung
Fachgebiet	Optimierung	Optimierung	Entscheidungsfindung	Optimierung
Familie	Process / pipeline	Process / pipeline	MCDM	Process / pipeline
Entstehungsjahr	2006	1957	1955	1947
Urheber	Rossi, van Beek & Walsh	Richard Bellman	Charnes, A., Cooper, W. W.	George B. Dantzig
Typ	Declarative combinatorial optimization	Exact combinatorial optimization via recursive decomposition	Multi-objective optimisation — weighted/lexicographic goal deviation minimisation	Mathematical programming / continuous optimization
Wegweisende Quelle	Rossi, F., van Beek, P., & Walsh, T. (Eds.). (2006). Handbook of Constraint Programming. Elsevier. ISBN: 978-0-444-52726-4	Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6	Charnes, A., Cooper, W. W. (1955). Optimal estimation of executive compensation by linear programming. Management Science	Dantzig, G.B. (1963). Linear Programming and Extensions. Princeton University Press. ISBN: 9780691059136
Aliasnamen	Constraint Satisfaction Programming, Constraint-Based Optimization, Kısıt Programlama, CSP Optimization	DP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama	—	LP, linear optimization, Doğrusal Programlama (LP)
Verwandt	3	3	8	4
Zusammenfassung	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.	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.	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.