Optimal aggregation of interval numbers based on genetic algorithm in group decision

Bingyi Kang, Yajuan Zhang, Xinyang Deng, Jiyi Wu, Xiaohong Sun, Ya Li, Yong Deng

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

A group of decision-makers may differ in their choice of alternatives while making a decision. As a result, how to aggregate opinions of different experts is still an open issue. Due to the uncertainty in the process of decision making, some mathematic tools such as fuzzy sets theory and evidence theory, are used to model uncertain information. In this paper, the experts' opinions are represented by interval numbers. A new optimal aggregation method to combine interval data is proposed based on genetic algorithm. The new method can deal with experts' opinions in an efficient manner. A numerical example on group decision making under uncertain environment is used to illustrate the efficiency of our proposed method.

Original languageEnglish
Pages (from-to)842-849
Number of pages8
JournalJournal of Information and Computational Science
Volume8
Issue number5
StatePublished - May 2011
Externally publishedYes

Keywords

  • Distance measure
  • Genetic algorithm
  • Group decision making
  • Interval number

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