Journal
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Volume 34, Issue 3, Pages 439-476Publisher
WILEY
DOI: 10.1002/int.22060
Keywords
aggregation operator; Bonferroni mean; multiple attribute decision making; q-rung orthopair fuzzy sets
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Funding
- National Natural Science Foundation of China [11401457]
- Postdoctoral Science Foundation of China [2015M582624]
- Shaanxi Province Postdoctoral Science Foundation of China
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The q-rung orthopair fuzzy sets are superior to intuitionistic fuzzy sets or Pythagorean fuzzy sets in expressing fuzzy and uncertain information. In this paper, some partitioned Bonferroni means (BMs) for q-rung orthopair fuzzy values have been developed. First, the q-rung orthopair fuzzy partitioned BM (q-ROFPBM) operator and the q-rung orthopair fuzzy partitioned geometric BM (q-ROFPGBM) operator are developed. Some desirable properties and some special cases of the new aggregation operators have been studied. The q-rung orthopair fuzzy weighted partitioned BM (q-ROFWPBM) operator and the q-rung orthopair fuzzy partitioned geometric weighted BM (q-ROFPGWBM) operator are also developed. Then, a new multiple-attribute decision-making method based on the q-ROFWPBM (q-ROFPGWBM) operator is proposed. Finally, a numerical example of investment company selection problem is given to illustrate feasibility and practical advantages of the new method.
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