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Evolving fuzzy rules for due-date assignment problem in semiconductor manufacturing factory

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Abstract

This paper presents a fuzzy modeling method proposed by Wang and Mendel for generation of fuzzy rules using data generated from a simulated model that is built from a real factory located in Hsin-Chu science-based park of Taiwan, R.O.C. The fuzzy modeling method is further evolved by a genetic algorithm for due-date assignment problem in manufacturing. By using simulated data, the effectiveness of the proposed method is shown and compared with two other soft computing techniques: multi-layer perceptron neural networks and case-based reasoning. The comparative results indicate that the proposed method is consistently superior to the other two methods.

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Authors and Affiliations

  1. Department of Industrial Engineering and Management, Yuan-Ze University, Taoyuan, Taiwan

    Pei-Chann Chang

  2. Department of Industrial Management, Vanung University, Chungli, Taiwan

    Jih-Chang Hieh

  3. Department of Industrial & Manufacturing Systems Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA

    T. Warren Liao

Authors
  1. Pei-Chann Chang
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  2. Jih-Chang Hieh
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  3. T. Warren Liao
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Chang, PC., Hieh, JC. & Liao, T.W. Evolving fuzzy rules for due-date assignment problem in semiconductor manufacturing factory. J Intell Manuf 16, 549–557 (2005). https://doi.org/10.1007/s10845-005-1663-4

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  • DOI: https://doi.org/10.1007/s10845-005-1663-4

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