Abstract
The development of low-level heuristics for solving instances of a problem is related to the knowledge of an expert. He needs to analyze several components from the problem instance and to think out an specialized heuristic for solving the instance. However if any inherent component to the instance gets changes, then the designed heuristic may not work as it used to do it. In this paper it is presented a novel approach to generated low-level heuristics; the proposed approach implements micro-Differential Evolution for evolving an indirect representation of the Bin Packing Problem. It was used the Hard28 instance, which is a well-known and referenced Bin Packing Problem instance. The heuristics obtained by the proposed approach were compared against the well know First-Fit heuristic, the results of packing that were gotten for each heuristic were analized by the statistic non-parametric test known as Wilcoxon Signed Rank test.
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Sotelo-Figueroa, M.A., Soberanes, H.J.P., Carpio, J.M., Fraire Huacuja, H.J., Reyes, L.C., Soria Alcaraz, J.A. (2013). Evolving Bin Packing Heuristic Using Micro-Differential Evolution with Indirect Representation. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Recent Advances on Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33021-6_28
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DOI: https://doi.org/10.1007/978-3-642-33021-6_28
Publisher Name: Springer, Berlin, Heidelberg
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