An evolutionary hyperheuristic to solve strip-packing problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 4881 LNCS, pages 406-415, 2007. abstract bibtex In this paper we introduce an evolutionary hyperheuristic approach to solve difficult strip packing problems. We have designed a genetic based hyperheuristic using the most recently proposed low-level heuristics in the literature. Two versions for tuning parameters have also been evaluated. The results obtained are very encouraging showing that our approach outperforms the single heuristics and others well-known techniques. © Springer-Verlag Berlin Heidelberg 2007.
@inproceedings{38449085011,
abstract = "In this paper we introduce an evolutionary hyperheuristic approach to solve difficult strip packing problems. We have designed a genetic based hyperheuristic using the most recently proposed low-level heuristics in the literature. Two versions for tuning parameters have also been evaluated. The results obtained are very encouraging showing that our approach outperforms the single heuristics and others well-known techniques. © Springer-Verlag Berlin Heidelberg 2007.",
year = "2007",
title = "An evolutionary hyperheuristic to solve strip-packing problems",
volume = "4881 LNCS",
pages = "406-415",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)"
}
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