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.
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Nguyen, S., Zhang, M., Johnston, M., Tan, K.C. (2012). Automatic Discovery of Optimisation Search Heuristics for Two Dimensional Strip Packing Using Genetic Programming. In: Bui, L.T., Ong, Y.S., Hoai, N.X., Ishibuchi, H., Suganthan, P.N. (eds) Simulated Evolution and Learning. SEAL 2012. Lecture Notes in Computer Science, vol 7673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34859-4_34
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DOI: https://doi.org/10.1007/978-3-642-34859-4_34
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