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Parameter Setting for Clonal Selection Algorithm in Facility Layout Problems

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Computational Science and Its Applications – ICCSA 2007 (ICCSA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4705))

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Abstract

The study introduces a Clonal Selection Algorithm (CSA), which depends on Artificial Immune System principles, for traditional facility layout problems. The CSA aims to minimize the total material handling cost between departments in a single manufacturing period. The determination of the optimum parameters for artificial intelligence algorithms is vital. Therefore a design of experiments study is made. The proposed algorithm is coded and tested by means test problems from literature based on the predefined parameters. The optimum solutions for small sized (5-8 department) layout problems are found. For larger (12, 15, 20, and 30 department) problems 1,077%, 5,703%, 1,126% and 3,671% improvements are obtained respectively. Better solutions are attained within shorter times compared with enumeration and CRAFT solutions.

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Authors and Affiliations

  1. Eskişehir Osmangazi University, Department of Industrial Engineering, Eskişehir, Turkey

    Berna Haktanirlar Ulutaş & A. Attila Işlier

Authors
  1. Berna Haktanirlar Ulutaş
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  2. A. Attila Işlier
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Osvaldo Gervasi Marina L. Gavrilova

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© 2007 Springer-Verlag Berlin Heidelberg

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Ulutaş, B.H., Işlier, A.A. (2007). Parameter Setting for Clonal Selection Algorithm in Facility Layout Problems. In: Gervasi, O., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2007. ICCSA 2007. Lecture Notes in Computer Science, vol 4705. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74472-6_72

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  • DOI: https://doi.org/10.1007/978-3-540-74472-6_72

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74468-9

  • Online ISBN: 978-3-540-74472-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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