期刊
PLOS ONE
卷 13, 期 3, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0193027
关键词
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资金
- National Natural Science Foundation of China [71771140, 71471172]
- Special Funds of Taishan Scholars Project of Shandong Province [ts201511045]
- Shandong Province Higher Educational Science and Technology Program [J16LN25, J17KA189]
- National Natural Science Foundation of China [71771140, 71471172]
- Special Funds of Taishan Scholars Project of Shandong Province [ts201511045]
- Shandong Province Higher Educational Science and Technology Program [J16LN25, J17KA189]
Linguistic neutrosophic numbers (LNNs) can easily describe the incomplete and indeterminate information by the truth, indeterminacy, and falsity linguistic variables (LVs), and the Hamy mean (HM) operator is a good tool to deal with multiple attribute group decision making (MAGDM) problems because it can capture the interrelationship among the multi-input arguments. Motivated by these ideas, we develop linguistic neutrosophic HM (LNHM) operator and weighted linguistic neutrosophic HM (WLNHM) operator. Some desirable properties and special cases of two operators are discussed in detail. Furthermore, considering the situation in which the decision makers (DMs) can't give the suitable weight of each attribute directly from various reasons, we propose the concept of entropy for linguistic neutrosophic set (LNS) to obtain the attribute weight vector objectively, and then the method for MAGDM problems with LNNs is proposed, and some examples are used to illustrate the effectiveness and superiority of the proposed method by comparing with the existing methods.
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