Journal
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
Volume 14, Issue 3, Pages 659-696Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0219622015500029
Keywords
Fuzzy logic; neural networks; excluded-mean; excluded-variance; variance influence function (VIF); group decision making
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Funding
- Natural Sciences and Engineering Research Council of Canada (NSERC) [RGPIN-170464, STPGP-365290, STPGP-350861, NNAPJ-376336]
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Many qualitative group decisions in professional fields such as law, engineering, economics, psychology, and medicine that appear to be crisp and certain are in reality shrouded in fuzziness as a result of uncertain environments and the nature of human cognition within which the group decisions are made. In this paper, we introduce an innovative approach to group decision making in uncertain situations by using fuzzy theory and a mean-variance neural approach. The key idea of this proposed approach is to defuzzify the fuzziness of the evaluation values from a group, compute the excluded-mean of individual evaluations and weight it by applying a variance influence function (VIF); this process of weighting the excluded-mean by VIF provides an improved result in the group decision making. In this paper, a case study with the proposed fuzzy-neural approach is also presented. The results of this case study indicate that this proposed approach can improve the er effectiveness of qualitative decision making by providing the decision maker with a new cognitive tool to assist in the reasoning process.
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