Journal
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
Volume 18, Issue 1, Pages 105-146Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0219622018500013
Keywords
Unbalanced linguistic term set; Maclaurin symmetric mean; multiple attribute decision-making
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Funding
- National Natural Science Foundation of China [71771140, 71471172]
- Special Funds of Taishan Scholars Project of Shandong Province [ts201511045]
- Shandong Provincial Social Science Planning Project [17BGLJ04, 16CGLJ31, 16CKJJ27]
- Teaching Reform Research Project of Undergraduate Colleges and Universities in Shandong Province [2015Z057]
- Science and Technology Project of Colleges and Universities of Shandong Province [J16LN25]
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In this paper, we firstly introduced the unbalanced linguistic term sets, the linguistic transforming methodology, the Maclaurin symmetric mean (MSM) operator and dual MSM (DMSM) operator. Then, we proposed the closed operational rules of unbalanced linguistic variables, and several new MSM aggregation operators, including unbalanced linguistic MSM (ULMSM) operator, weighted unbalanced linguistic MSM (WULMSM) operator, unbalanced linguistic DMSM (ULDMSM) operator and weighted unbalanced linguistic DMSM (WULDMSM) operator. Further, we proposed two multiple attribute decision-making (MADM) methods under unbalanced linguistic environments based on the WULMSM operator and WULDMSM operator, respectively. Finally, a numerical example is used to show the applicability and effectiveness of the proposed MADM methods and to reveal their advantages by comparing with the existing methods.
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