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The analysis of discrete artificial bee colony algorithm with neighborhood operator on traveling salesman problem

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Abstract

The artificial bee colony (ABC) algorithm, inspired intelligent behaviors of real honey bee colonies, was introduced by Karaboğa for numerical function optimization. The basic ABC has high performance and accuracy, if the solution space of the problem is continuous. But when the solution space of the problem is discrete, the basic ABC algorithm should be modified to solve this class optimization problem. In this study, we focused on analysis of discrete ABC with neighborhood operator for well-known traveling salesman problem and different discrete neighborhood operators are replaced with solution updating equations of the basic ABC. Experimental computations show that the promising results are obtained by the discrete version of the basic ABC and which neighborhood operator is better than the others. Also, the results obtained by discrete ABC were enriched with 2- and 3-opt heuristic approaches in order to increase quality of the solutions.

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Acknowledgments

The authors thank anonymous reviewers for their valuable comments and contributions and “Selcuk University Scientific Research Project Coordinatorship” and “The Scientific and Technological Research Council of Turkey” for their institutional supports.

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Authors and Affiliations

  1. Department of Computer Engineering, Faculty of Engineering and Architecture, Selcuk University, 42075, Konya, Turkey

    Mustafa Servet Kıran, Hazım İşcan & Mesut Gündüz

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  1. Mustafa Servet Kıran
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  2. Hazım İşcan
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  3. Mesut Gündüz
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Correspondence to Mustafa Servet Kıran.

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Kıran, M.S., İşcan, H. & Gündüz, M. The analysis of discrete artificial bee colony algorithm with neighborhood operator on traveling salesman problem. Neural Comput & Applic 23, 9–21 (2013). https://doi.org/10.1007/s00521-011-0794-0

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  • DOI: https://doi.org/10.1007/s00521-011-0794-0

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