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A Discrete Artificial Bee Colony Algorithm Based on Similarity for Graph Coloring Problems

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Theory and Practice of Natural Computing (TPNC 2016)

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Abstract

In this paper, a novel non-hybrid discrete artificial bee colony (ABC) algorithm is proposed for solving planar graph coloring problems. The original ABC intends to handle only continuous optimization problems. To apply ABC to discrete problems, the original ABC operators need to be redefined over discrete space. In this work, a new algorithm based on Similarity is introduced. Compared with HDPSO, the experiment shows that the proposed method matches the competitive results and obtains higher success rate and lower average evaluation times when solving planar graph coloring problems.

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Acknowledgments

The authors wish to thank Dr. Claus Aranha of University of Tsukuba for his helpful comments and suggestions. This work is supported by JSPS KAKENHI Grant Number 15K00296.

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Correspondence to Kui Chen .

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Chen, K., Kanoh, H. (2016). A Discrete Artificial Bee Colony Algorithm Based on Similarity for Graph Coloring Problems. In: Martín-Vide, C., Mizuki, T., Vega-Rodríguez, M. (eds) Theory and Practice of Natural Computing. TPNC 2016. Lecture Notes in Computer Science(), vol 10071. Springer, Cham. https://doi.org/10.1007/978-3-319-49001-4_6

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  • DOI: https://doi.org/10.1007/978-3-319-49001-4_6

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