Two look-ahead strategies for local-search metaheuristics
Autor(en): | Meignan, D. Schwarze, S. Voß, S. |
Stichwörter: | Artificial intelligence; Computer science; Computers, Hyperheuristic; Hyper-heuristic; Iterated local-search; Look-ahead; Meta heuristics; Metaheuristic; Problem instances, Heuristic methods | Erscheinungsdatum: | 2014 | Herausgeber: | Springer Verlag | Journal: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Volumen: | 8426 LNCS | Startseite: | 187 | Seitenende: | 202 | Zusammenfassung: | The main principle of a look-ahead strategy is to inspect a few steps ahead before taking a decision on the direction to choose. We propose two original look-ahead strategies that differ in the object of inspection. The first method introduces a look-ahead mechanism at a superior level for selecting local-search operators. The second method uses a look-ahead strategy on a lower level in order to detect promising solutions for further improvement. The proposed approaches are implemented using a hyper-heuristic framework and tested against alternative methods. Furthermore, a more detailed investigation of the second method is added and gives insight on the influence of parameter values. The experiments reveal that the introduction of a simple look-ahead strategy into an iterated local-search procedure significantly improves the results over tested problem instances. © 2014 Springer International Publishing. |
Beschreibung: | Conference of 8th International Conference on Learning and Intelligent OptimizatioN, LION 2014 ; Conference Date: 16 February 2014 Through 21 February 2014; Conference Code:106870 |
ISBN: | 9783319095837 | ISSN: | 03029743 | DOI: | 10.1007/978-3-319-09584-4_18 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84905836874&doi=10.1007%2f978-3-319-09584-4_18&partnerID=40&md5=bfc2f2a1cb5d8d77a090248590355031 |
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