Solving bin packing problem with a hybridization of hard computing and soft computing

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Abstract

This paper presents a new hybrid intelligent system that solves the Bin Packing Problem. The methodology involves the fusion of Soft Computing by means a genetic algorithm and Hard Computing using limits criterion and deterministic strategies. The innovative proposal inverts minimum computational resources expressed in generations with a high level quality solution and shows the algorithm performance with statistical methods. The average theoretical ratio for 1370 standard instances was 1.002 and the best known solution was achieved in 83.72% of the cases. As future work, an exhaustive analysis of characteristics of the hardest instances is proposed; the purpose is to find new hybrid methods. © 2007 Springer-Verlag Berlin Heidelberg.

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APA

Cruz-Reyes, L., Nieto-Yáñez, D. M., Tomás-solis, P., & Valdez, G. C. (2007). Solving bin packing problem with a hybridization of hard computing and soft computing. In Advances in Soft Computing (Vol. 44, pp. 223–230). https://doi.org/10.1007/978-3-540-74972-1_30

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