Abstract
Grammatical Evolution has been used to evolve heuristics for the Bin Packing Problem. It has been shown that the use of Grammatical Evolution can generate an heuristic for either one instances or a full instance set for this problem. In many papers the selection of instances for heuristics generation has been done randomly. The present work proposes a methodology to cluster bin packing instances and choose the instances to generate an heuristic for each cluster. The number of heuristics generated is based on the number of clusters. There were used only one instance by cluster. The results obtained were compared through non-parametric tests against the best known heuristics.
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Acknowledgement
Authors thanks the support received from Consejo Nacional de Ciencia y Tecnologia (CONACyT).The authors want to thank to Instituto Tecnológico de León (ITL) for the support to this research. Additionally they want to aknowledge the generous support from the Mexican National Council for Science and Technology (CONACyT) for this research project.
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Sotelo-Figueroa, M.A., Puga Soberanes, H.J., Carpio, J.M., Fraire Huacuja, H.J., Reyes, L.C., Soria Alcaraz, J.A. (2015). Clustering Bin Packing Instances for Generating a Minimal Set of Heuristics by Using Grammatical Evolution. In: Castillo, O., Melin, P. (eds) Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics. Studies in Computational Intelligence, vol 574. Springer, Cham. https://doi.org/10.1007/978-3-319-10960-2_10
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