Genetic Programming of Fuzzy Aggregation Operations

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{musilek:2005:JIFS,
  author =       "Petr Musilek and Rhea Guanlao and Guillermo Barreiro",
  title =        "Genetic Programming of Fuzzy Aggregation Operations",
  journal =      "Journal of Intelligent and Fuzzy Systems",
  year =         "2005",
  volume =       "16",
  number =       "2",
  pages =        "107--118",
  email =        "musilek@ece.ualberta.ca",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1064-1246",
  URL =          "http://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs00253",
  size =         "12 pages",
  abstract =     "Aggregation operations play an important role in
                 decision-making problems where a weighted combination
                 of several criteria is used to select an alternative
                 with the strongest support. In fuzzy set theory,
                 aggregation operations are usually modelled as
                 intersection, union, or as combination of both. The
                 particular form and algebraic properties of these
                 operations vary according to requirements for
                 compensation among the criteria and other
                 characteristics of the given decision-making situation.
                 Traditionally, only algebraically well-behaved
                 operations have been considered for this purpose. By
                 relaxing some algebraic constraints, more realistic
                 operations can be obtained that closely capture certain
                 features of human decision-making, such as preferences
                 and a limited level of detail.

                 proposes a method to generate fuzzy aggregation
                 operations using genetic programming. It is shown that
                 an evolutionary process, facilitated by genetic
                 programming, has the capacity to generate new valid
                 fuzzy aggregation operations and to reproduce existing
                 ones. By varying process conditions, encoded in a
                 fitness function, it is possible to obtain operations
                 with different logical and algebraic properties. This
                 approach, based solely on the axioms which define the
                 desired class of operations, explores the space of
                 possible functions and often leads to discovery of new
                 operations. However, the proposed system can also be
                 used to generate aggregation operations that fit a
                 collected data set. This application is very important
                 as it provides a powerful new tool for modelling and
                 processing empirical data.",
  notes =        "http://www.iospress.nl/html/10641246.php",
}

Genetic Programming entries for Petr Musilek Rhea Guanlao Guillermo Barreiro

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