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A Prioritized Information Fusion Method for Handling Fuzzy Decision-Making Problems

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Abstract

Although Yager has presented a prioritized operator for fuzzy subsets, called the non-monotonic operator, it can not be used to deal with multi-criteria fuzzy decision-making problems when generalized fuzzy numbers are used to represent the evaluating values of criteria. In this paper, we present a prioritized information fusion algorithm based on the similarity measure of generalized fuzzy numbers. The proposed prioritized information fusion algorithm has the following advantages: (1) It can handle prioritized multi-criteria fuzzy decision-making problems in a more flexible manner due to the fact that it allows the evaluating values of criteria to be represented by generalized fuzzy numbers or crisp values between zero and one, and (2) it can deal with prioritized information filtering problems based on generalized fuzzy numbers.

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  1. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, Republic of China

    Shi-Jay Chen & Shyi-Ming Chen

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  1. Shi-Jay Chen
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  2. Shyi-Ming Chen
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Correspondence to Shyi-Ming Chen.

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Chen, SJ., Chen, SM. A Prioritized Information Fusion Method for Handling Fuzzy Decision-Making Problems. Appl Intell 22, 219–232 (2005). https://doi.org/10.1007/s10791-005-6620-5

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