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An Artificial Neural Network Based Simulation Metamodeling Approach for Dual Resource Constrained Assembly Line

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Artificial Neural Networks – ICANN 2006 (ICANN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4132))

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Abstract

The main objective of this study is to find the optimum values of design and operational parameters related to worker flexibility in a Dual Resource Constrained (DRC) assembly line considering the performance measures of Hourly Production Rate (HPR), Throughput Time (TT) and Number of Worker Transfers (NWT). We used Artificial Neural Networks (ANN) as a simulation metamodel to estimate DRC assembly line performances for all possible alternatives. All alternatives were evaluated with respect to a utility function which consists of weighted sum of normalized performance measures.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Industrial Engineering Dept., Dokuz Eylul University, 35100, Bornova-Izmir, Turkey

    Gokalp Yildiz & Ozgur Eski

Authors
  1. Gokalp Yildiz
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  2. Ozgur Eski
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Editor information

Editors and Affiliations

  1. School of Electrical and Computer Engineering, Image, Video and Multimedia Systems Laboratory, National Technical University of Athens, 157 80, Zographou, GR, Greece

    Stefanos Kollias

  2. Department of Electrical and Computer Engineering, National Technical University of Athens, 15780, Zographou, Greece

    Andreas Stafylopatis

  3. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  4. Adaptive Informatics Research Centre, Helsinki University of Technology, P.O. Box 5400, 02015, HUT, Finland

    Erkki Oja

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© 2006 Springer-Verlag Berlin Heidelberg

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Yildiz, G., Eski, O. (2006). An Artificial Neural Network Based Simulation Metamodeling Approach for Dual Resource Constrained Assembly Line. In: Kollias, S., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840930_104

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  • DOI: https://doi.org/10.1007/11840930_104

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38871-5

  • Online ISBN: 978-3-540-38873-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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