Maximizing deviation method for neutrosophic multiple attribute decision making with incomplete weight information

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dc.authorid56285350800
dc.authorid35388763600
dc.contributor.authorŞahin R.
dc.contributor.authorLiu P.
dc.date.accessioned20.04.201910:49:12
dc.date.accessioned2019-04-20T21:43:30Z
dc.date.available20.04.201910:49:12
dc.date.available2019-04-20T21:43:30Z
dc.date.issued2016
dc.departmentBayburt Üniversitesien_US
dc.description.abstractThis paper develops a method for solving the multiple attribute decision-making problems with the single-valued neutrosophic information or interval neutrosophic information. We first propose two discrimination functions referred to as score function and accuracy function for ranking the neutrosophic numbers. An optimization model to determine the attribute weights that are partly known is established based on the maximizing deviation method. For the special situations where the information about attribute weights is completely unknown, we propose another optimization model. A practical and useful formula which can be used to determine the attribute weights is obtained by solving a proposed nonlinear optimization problem. To aggregate the neutrosophic information corresponding to each alternative, we utilize the neutrosophic weighted averaging operators which are the single-valued neutrosophic weighted averaging operator and the interval neutrosophic weighted averaging operator. Thus, we can determine the order of alternatives and choose the most desirable one(s) based on the score function and accuracy function. Finally, some illustrative examples are presented to verify the proposed approach and to present its effectiveness and practicality. © 2015, The Natural Computing Applications Forum.en_US
dc.identifier.doi10.1007/s00521-015-1995-8
dc.identifier.endpage2029
dc.identifier.issn0941-0643
dc.identifier.issue7
dc.identifier.scopus2-s2.0-84938530645en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2017
dc.identifier.urihttps://dx.doi.org/10.1007/s00521-015-1995-8
dc.identifier.urihttps://hdl.handle.net/20.500.12403/580
dc.identifier.volume27
dc.identifier.wosWOS:000382131300018en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer-Verlag London Ltd
dc.relation.ispartofNeural Computing and Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAggregation operators
dc.subjectInterval neutrosophic sets
dc.subjectMaximizing deviation method
dc.subjectNeutrosophic multiple attribute decision making
dc.subjectNeutrosophic sets
dc.subjectSingle-valued neutrosophic sets
dc.subjectMathematical operators
dc.subjectNonlinear programming
dc.subjectOptimization
dc.subjectStatistical methods
dc.subjectAggregation operator
dc.subjectInterval neutrosophic sets
dc.subjectMaximizing deviation method
dc.subjectMultiple attribute decision making
dc.subjectNeutrosophic sets
dc.subjectDecision making
dc.subjectAggregation operators
dc.subjectInterval neutrosophic sets
dc.subjectMaximizing deviation method
dc.subjectNeutrosophic multiple attribute decision making
dc.subjectNeutrosophic sets
dc.subjectSingle-valued neutrosophic sets
dc.subjectMathematical operators
dc.subjectNonlinear programming
dc.subjectOptimization
dc.subjectStatistical methods
dc.subjectAggregation operator
dc.subjectInterval neutrosophic sets
dc.subjectMaximizing deviation method
dc.subjectMultiple attribute decision making
dc.subjectNeutrosophic sets
dc.subjectDecision making
dc.titleMaximizing deviation method for neutrosophic multiple attribute decision making with incomplete weight informationen_US
dc.typeArticleen_US

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