Multiple attribute group decision making method based on interval-valued intuitionistic fuzzy power Heronian aggregation operators

•We proposed some PHA operators by combining power-average and Heronian mean.•We investigated some desirable properties of these operators.•We studied some special cases of these operators.•We developed a MAGDM method based these operators.•We gave the advantages of proposed method by comparing with...

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Veröffentlicht in:	Computers & industrial engineering Jg. 108; S. 199 - 212
1. Verfasser:	Liu, Peide
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.06.2017
Schlagworte:	Heronian mean Interval-valued intuitionistic fuzzy power weighted Heronian aggregation (IVIFPWHA) operator Interval-valued intuitionistic fuzzy set Multiple attribute group decision making Power average operator Interval-valued intuitionistic fuzzy set Heronian mean Interval-valued intuitionistic fuzzy power weighted Heronian aggregation (IVIFPWHA) operator Multiple attribute group decision making Power average operator
ISSN:	0360-8352
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Zusammenfassung:	•We proposed some PHA operators by combining power-average and Heronian mean.•We investigated some desirable properties of these operators.•We studied some special cases of these operators.•We developed a MAGDM method based these operators.•We gave the advantages of proposed method by comparing with the existing methods. The power average operator can relieve the some influences of unreasonable data given by biased decision makers, and Heronian mean operator can consider the interrelationship of the aggregated arguments. In order to take full advantages of these two kinds of operators, in this paper, we combined the power average operator with Heronian mean operator and extended them to process interval-valued intuitionistic fuzzy information, and proposed the interval-valued intuitionistic fuzzy power Heronian aggregation (IVIFPHA) operator, interval-valued intuitionistic fuzzy power weight Heronian aggregation (IVIFPWHA) operator. At the same time, we presented a new similarity function of IVIFNs as support degree in power weighting, and it has a good reliability and accuracy. Further, some properties of these new aggregation operators are investigated and some special cases are discussed, and a new technique based on these operators for fuzzy multiple attribute group decision making (MAGDM) was presented. Finally, an illustrative example was given to illustrate the effectiveness and advantages of the developed method by comparing with the existing methods.
ISSN:	0360-8352
DOI:	10.1016/j.cie.2017.04.033