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Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Ντετερμινιστικός Προγραμματισμός Μικτών Ακεραίων× | Προγραμματισμός Μικτών Ακέραιων Τιμών× | |
|---|---|---|
| Πεδίο | Προσομοίωση | Προσομοίωση |
| Οικογένεια | Process / pipeline | Process / pipeline |
| Έτος προέλευσης | 1958–1960 | 1958–1960 |
| Δημιουργός≠ | 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) |
| Τύπος≠ | Mathematical programming / combinatorial optimization | Mathematical optimization |
| Θεμελιώδης πηγή≠ | 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 |
| Εναλλακτικές ονομασίες | Deterministic MIP, Deterministic MILP/MIQP, Classical Mixed-Integer Programming, Deterministic MIP Optimization | MIP, Mixed-Integer Linear Programming, MILP, Integer Programming |
| Συναφείς | 6 | 6 |
| Σύνοψη≠ | 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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