Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Hiperheuristikas× | Tabu Search× | |
|---|---|---|
| Nozare | Optimizācija | Optimizācija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 2013 | 1989 |
| Autors≠ | Burke et al. | Fred Glover |
| Tips≠ | High-level search methodology | Local-search metaheuristic |
| Pirmavots≠ | 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 ↗ | Glover, F. (1989). Tabu Search — Part I. ORSA Journal on Computing, 1(3), 190–206. link ↗ |
| Citi nosaukumi≠ | Heuristic of Heuristics, Algorithm Selection Hyper-Heuristic, Selection Hyper-Heuristic, Hiyer-Sezgisel | Tabu Araması (Tabu Search), TS, tabu metaheuristic |
| Saistītās≠ | 3 | 4 |
| Kopsavilkums≠ | 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. | Tabu Search is a local-search metaheuristic introduced by Fred Glover in 1989 that uses a tabu list — a short-term memory of recently visited solutions — to prevent cycling and escape local optima. By explicitly forbidding moves that reverse recent decisions, the algorithm explores the search space more broadly and, through long-term memory structures such as aspiration criteria, aims to approach the global optimum even in large, complex combinatorial problems. |
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