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| Динамично оптимиране× | Программиране с целеви стойности (Goal Programming)× | Линейно оптимиране× | |
|---|---|---|---|
| Област≠ | Оптимизация | Вземане на решения | Оптимизация |
| Семейство≠ | Process / pipeline | MCDM | Process / pipeline |
| Година на възникване≠ | 1957 | 1955 | 1947 |
| Създател≠ | Richard Bellman | Charnes, A., Cooper, W. W. | George B. Dantzig |
| Тип≠ | Exact combinatorial optimization via recursive decomposition | Multi-objective optimisation — weighted/lexicographic goal deviation minimisation | Mathematical programming / continuous optimization |
| Основополагащ източник≠ | 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 DOI ↗ | Dantzig, G.B. (1963). Linear Programming and Extensions. Princeton University Press. ISBN: 9780691059136 |
| Други названия≠ | DP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama | — | LP, linear optimization, Doğrusal Programlama (LP) |
| Свързани≠ | 3 | 8 | 4 |
| Резюме≠ | 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. |
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