Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Deterministické programování s celočíselnými proměnnými× | Programování se smíšenými celočíselnými proměnnými× | |
|---|---|---|
| Obor | Simulace | Simulace |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku | 1958–1960 | 1958–1960 |
| Tvůrce≠ | Gomory, R. E.; Dantzig, G. B.; Land, A. H.; Doig, A. G. | Ralph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960) |
| Typ≠ | Mathematical programming / combinatorial optimization | Mathematical optimization |
| Původní zdroj≠ | Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. John Wiley & Sons, New York. ISBN: 9780471359432 | Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. Wiley-Interscience, New York. ISBN: 9780471359432 |
| Další názvy | Deterministic MIP, Deterministic MILP/MIQP, Classical Mixed-Integer Programming, Deterministic MIP Optimization | MIP, Mixed-Integer Linear Programming, MILP, Integer Programming |
| Příbuzné | 6 | 6 |
| Shrnutí≠ | Deterministic Mixed-Integer Programming (MIP) is a mathematical optimization framework that finds the provably optimal solution to problems involving both continuous and integer decision variables under fully known, fixed coefficients and constraints. It is the foundational workhorse of operations research when all data are treated as certain. | Mixed-Integer Programming (MIP) is a mathematical optimization framework in which some decision variables must take integer values while others may be continuous. It generalizes linear programming and is widely used in operations research, logistics, scheduling, resource allocation, and engineering design, where indivisibility constraints — such as yes/no decisions or whole-unit quantities — arise naturally. |
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