Composite fuzzy measure and its application to decision-making

Toshihiro Kaino*, Kaoru Hirota

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In applications using fuzzy measures (on real numbers), it becomes a problem how to evaluate inbetween intervals each characterized by a fuzzy measure, especially when the Choquet integral is differentiated in real world problems. A composite fuzzy measure built from fuzzy measures defined on fuzzy measurable spaces has been proposed by Kaino and Hirota using composite fuzzy weights, where the measurable space of this composite fuzzy measure is the direct sum of measurable spaces. An associative, composite fuzzy measure built from a finite number of fuzzy measures is proposed and, in a constructive application, it is applied to the automobile plant capital investment decision-making problem. It is assumed that an automobile company plans to sell a new car. The current plant line has a capacity of 3,200 new cars in addition to current car lines. Using this composite fuzzy measure, differentiation of the Choquet integral becomes a quantitative index for decision-making, which is confirmed by this decision-making experiment.

Original languageEnglish
Pages (from-to)252-259
Number of pages8
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume8
Issue number3
DOIs
Publication statusPublished - May 2004
Externally publishedYes

Keywords

  • Associative
  • Choquet integral
  • Decision-making
  • Differentiation
  • composite fuzzy measure

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