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International Fuzzy Systems Association World Congress

IFSA 2007: Foundations of Fuzzy Logic and Soft Computing pp 371–380Cite as

On Selecting an Algorithm for Fuzzy Optimization

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNAI,volume 4529)

Abstract

Formulations for fuzzy and possibilistic optimization abound in the literature, but few are implemented in practice. This paper investigates the theory, semantics, and efficacy of a selection of significant fuzzy and possibilistic optimization algorithms via their application to a well-known large-scale problem: the radiation therapy planning problem. The algorithms are compared, critiqued, and organized with the following objective in mind: to guide a decision maker in the selection and implementation of a fuzzy or possibilistic optimization algorithm.

Keywords

  • Fuzzy
  • Possibilistic
  • Optimization
  • Algorithm

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Author information

Authors and Affiliations

  1. Department of Mathematical Sciences, University of Colorado at Denver,  

    Elizabeth Untiedt & Weldon Lodwick

Authors
  1. Elizabeth Untiedt
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  2. Weldon Lodwick
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Editor information

Patricia Melin Oscar Castillo Luis T. Aguilar Janusz Kacprzyk Witold Pedrycz

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© 2007 Springer Berlin Heidelberg

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Untiedt, E., Lodwick, W. (2007). On Selecting an Algorithm for Fuzzy Optimization. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds) Foundations of Fuzzy Logic and Soft Computing. IFSA 2007. Lecture Notes in Computer Science(), vol 4529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72950-1_37

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  • DOI: https://doi.org/10.1007/978-3-540-72950-1_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72917-4

  • Online ISBN: 978-3-540-72950-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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