Applications of fuzzy sets in industrial engineering: A topical classification

Cengiz Kahraman*, Murat Gülbay, Özgür Kabak

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

62 Citations (Scopus)

Abstract

A rational approach toward decision-making should take into account human subjectivity, rather than employing only objective probability measures. This attitude towards the uncertainty of human behavior led to the study of a relatively new decision analysis field: Fuzzy decision-making. Fuzzy systems are suitable for uncertain or approximate reasoning, especially for the system with a mathematical model that is difficult to derive. Fuzzy logic allows decision-making with estimated values under incomplete or uncertain information. A major contribution of fuzzy set theory is its capability of representing vague data. Fuzzy set theory has been used to model systems that are hard to define precisely. As a methodology, fuzzy set theory incorporates imprecision and subjectivity into the model formulation and solution process. Fuzzy set theory represents an attractive tool to aid research in industrial engineering (IE) when the dynamics of the decision environment limit the specification of model objectives, constraints and the precise measurement of model parameters. This chapter provides a survey of the applications of fuzzy set theory in IE.

Original languageEnglish
Pages (from-to)1-55
Number of pages55
JournalStudies in Fuzziness and Soft Computing
Volume201
DOIs
Publication statusPublished - 2006

Keywords

  • Artificial intelligence
  • Decision-making
  • Engineering economics
  • Ergonomics
  • Fuzzy sets
  • Industrial engineering
  • Manufacturing
  • Multiple criteria
  • Production planning
  • Quality management
  • Research areas

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