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Fuzzy Modeling and Optimization: Theory and Methods

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Data Mining

Part of the book series: Decision Engineering ((DECENGIN))

Abstract

After introducing definitions, properties and the foundation of fuzzy sets theory, this chapter aims to present a brief summary of the theory and methods of fuzzy optimization. We also attempt to give readers a clear and comprehensive understanding of knowledge, from the viewpoint of fuzzy modeling and fuzzy optimization, classification and formulation for the fuzzy optimization problems, models, and some well-known methods. The importance of interpretation of the problem and formulation of an optimal solution in a fuzzy sense are emphasized.

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Authors and Affiliations

  1. Department of Economics and Business Management, Yamagata University, 1-4-12, Kojirakawa-cho, 990-8560, Yamagata-shi, Japan

    Yong Yin

  2. Department of Management Science and Engineering, Akita Prefectural University, 015-0055, Yulihonjo, Japan

    Ikou Kaku

  3. Department of Systems Engineering, Northeastern University, 110006, Shenyang, China

    Jiafu Tang

  4. School of Information, Central University of Finance and Economics, Beijing, China

    JianMing Zhu

Authors
  1. Yong Yin
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  2. Ikou Kaku
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  3. Jiafu Tang
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  4. JianMing Zhu
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Yin, Y., Kaku, I., Tang, J., Zhu, J. (2011). Fuzzy Modeling and Optimization: Theory and Methods. In: Data Mining. Decision Engineering. Springer, London. https://doi.org/10.1007/978-1-84996-338-1_3

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  • DOI: https://doi.org/10.1007/978-1-84996-338-1_3

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84996-337-4

  • Online ISBN: 978-1-84996-338-1

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