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| Heltalsprogrammering× | Målprogrammering× | Lineær programmering× | |
|---|---|---|---|
| Fagområde≠ | Optimering | Beslutningstagning | Optimering |
| Familie≠ | Process / pipeline | MCDM | Process / pipeline |
| Oprindelsesår≠ | 1958 | 1955 | 1947 |
| Ophavsperson≠ | Ralph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960) | Charnes, A., Cooper, W. W. | George B. Dantzig |
| Type≠ | Mathematical optimisation — exact combinatorial method | Multi-objective optimisation — weighted/lexicographic goal deviation minimisation | Mathematical programming / continuous optimization |
| Oprindelig kilde≠ | Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669 | 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 |
| Aliasser≠ | IP, MIP, mixed-integer programming, mixed-integer linear programming | — | LP, linear optimization, Doğrusal Programlama (LP) |
| Relaterede≠ | 4 | 8 | 4 |
| Resumé≠ | 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. | 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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