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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2016: Artificial Intelligence and Soft Computing pp 311–320Cite as

Cyclic Scheduling Line with Uncertain Data

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9692))

Abstract

In this paper, a cyclic permutation flow shop problem for a certain production line with uncertain data is considered. The goal is to minimize the cycle time. The uncertain elements in the system are identified and modeled as fuzzy numbers. A metaheuristic fuzzy-aware algorithm is developed and tested against 3 deterministic algorithms. The fuzzy algorithm significantly outperforms deterministic algorithms 70 % of the time with similar computation time. The fuzzy algorithm is also more reliable, providing solutions with smaller standard deviation.

This work was co-financed by the Młoda Kadra, grant no. B50298.

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References

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Author information

Authors and Affiliations

  1. Department of Control Systems and Mechatronics, Wrocław University of Science and Technology, Janiszewskiego 11-17, 50-372, Wrocław, Poland

    Jarosław Rudy

Authors
  1. Jarosław Rudy
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Correspondence to Jarosław Rudy .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Czestochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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© 2016 Springer International Publishing Switzerland

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Rudy, J. (2016). Cyclic Scheduling Line with Uncertain Data. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9692. Springer, Cham. https://doi.org/10.1007/978-3-319-39378-0_27

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  • DOI: https://doi.org/10.1007/978-3-319-39378-0_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39377-3

  • Online ISBN: 978-3-319-39378-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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