Collaboration between hyperheuristics to solve strip-packing problems
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 4529 LNAI, Page: 698-707
2007
- 12Citations
- 10Captures
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Conference Paper Description
In this paper we introduce a collaboration framework for hyperheuristics to solve hard strip packing problems. We have designed a genetic based hyperheuristic to cooperate with a hill-climbing based hyper heuristic. Both of them use the most recently proposed low-level heuristics in the literature. REVAC, which has recently been proposed for tuning [18], has been used to find the best operators parameter values. The results obtained are very encouraging and have improved the results from both the single heuristics and the single hyperheuristics' tests. Thus, we conclude that the collaboration among hyperheuristics is a good way to solve hard strip packing problems. © Springer-Verlag Berlin Heidelberg 2007.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=37249019153&origin=inward; http://dx.doi.org/10.1007/978-3-540-72950-1_69; http://link.springer.com/10.1007/978-3-540-72950-1_69; http://link.springer.com/content/pdf/10.1007/978-3-540-72950-1_69.pdf; https://dx.doi.org/10.1007/978-3-540-72950-1_69; https://link.springer.com/chapter/10.1007/978-3-540-72950-1_69; http://www.springerlink.com/index/10.1007/978-3-540-72950-1_69; http://www.springerlink.com/index/pdf/10.1007/978-3-540-72950-1_69
Springer Science and Business Media LLC
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