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

Show full item record

Page view(s)

2
Last Week
0
Last month
1
checked on May 19, 2024

Google ScholarTM

Check

Altmetric