Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-34859-4_34
Title: Automatic discovery of optimisation search heuristics for two dimensional strip packing using genetic programming
Authors: Nguyen, S.
Zhang, M.
Johnston, M.
Tan, K.C. 
Keywords: bin packing
genetic programming
heuristics
Issue Date: 2012
Source: Nguyen, S.,Zhang, M.,Johnston, M.,Tan, K.C. (2012). Automatic discovery of optimisation search heuristics for two dimensional strip packing using genetic programming. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7673 LNCS : 341-350. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-34859-4_34
Abstract: This paper presents a genetic programming based hyper-heuristic (GPHH) for automatic discovery of optimisation heuristics for the two dimensional strip packing problem (2D-SPP). The novelty of this method is to integrate both the construction and improvement procedure into a heuristic which can be evolved by genetic programming (GP). The experimental results show that the evolved heuristics are very competitive and sometimes better than the popular state-of-the-art optimisation search heuristics for 2D-SPP. Moreover, the evolved heuristics can search for good packing solutions in a much more efficient way compared to the other search methods. © 2012 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/69471
ISBN: 9783642348587
ISSN: 03029743
DOI: 10.1007/978-3-642-34859-4_34
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