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| Hyper-Heuristiken× | Ganzzahlige Programmierung× | |
|---|---|---|
| Fachgebiet | Optimierung | Optimierung |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 2013 | 1958 |
| Urheber≠ | Burke et al. | Ralph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960) |
| Typ≠ | High-level search methodology | Mathematical optimisation — exact combinatorial method |
| Wegweisende Quelle≠ | Burke, E. K., et al. (2013). Hyper-heuristics: A survey of the state of the art. Journal of the Operational Research Society, 64(12), 1695–1724. DOI ↗ | Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669 |
| Aliasnamen≠ | Heuristic of Heuristics, Algorithm Selection Hyper-Heuristic, Selection Hyper-Heuristic, Hiyer-Sezgisel | IP, MIP, mixed-integer programming, mixed-integer linear programming |
| Verwandt≠ | 3 | 4 |
| Zusammenfassung≠ | Hyper-heuristics are high-level methodologies that search over a space of heuristics rather than directly over the space of solutions. Introduced systematically by Burke et al. (2013) in their landmark survey, hyper-heuristics operate by selecting or generating low-level heuristics to solve hard combinatorial optimisation and search problems, aiming to automate the design of optimisation algorithms across diverse problem domains without requiring deep problem-specific knowledge. | 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. |
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