Diversification-driven tabu search for unconstrained binary quadratic problems
| Autor: | Fred S. Glover, Zhipeng Lü, Jin-Kao Hao |
|---|---|
| Přispěvatelé: | Laboratoire d'Etudes et de Recherche en Informatique d'Angers (LERIA), Université d'Angers (UA) |
| Jazyk: | angličtina |
| Rok vydání: | 2010 |
| Předmět: |
Mathematical optimization
021103 operations research 0211 other engineering and technologies Binary quadratic programming Binary number 02 engineering and technology Management Science and Operations Research Diversification (marketing strategy) Tabu search Theoretical Computer Science Management Information Systems Quadratic equation Computational Theory and Mathematics 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Guided Local Search [INFO]Computer Science [cs] Heuristics Algorithm ComputingMilieux_MISCELLANEOUS Mathematics |
| Zdroj: | 4OR: A Quarterly Journal of Operations Research 4OR: A Quarterly Journal of Operations Research, Springer Verlag, 2010, 8 (3), pp.239-253. ⟨10.1007/s10288-009-0115-y⟩ |
| ISSN: | 1619-4500 1614-2411 |
| DOI: | 10.1007/s10288-009-0115-y⟩ |
| Popis: | This paper describes a Diversification-Driven Tabu Search (D2TS) algorithm for solving unconstrained binary quadratic problems. D2TS is distinguished by the introduction of a perturbation-based diversification strategy guided by long-term memory. The performance of the proposed algorithm is assessed on the largest instances from the ORLIB library (up to 2500 variables) as well as still larger instances from the literature (up to 7000 variables). The computational results show that D2TS is highly competitive in terms of both solution quality and computational efficiency relative to some of the best performing heuristics in the literature. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink