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International Journal for Uncertainty Quantification

Impact factor: 1.000

ISSN Print: 2152-5080
ISSN Online: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2017020126
pages 355-376

A NOVEL MULTI-CRITERIA GROUP DECISION-MAKING APPROACH USING SIMPLIFIED NEUTROSOPHIC INFORMATION

Juan-Juan Peng
School of Economics and Management, Hubei University of Automotive Technology, Shiyan, China, 442002; School of Business, Central South University, Changsha, China, 410083
Jian-Qiang Wang
School of Business, Central South University, Changsha, China, 410083
Li-Jun Yang
School of Economics and Management, Hubei University of Automotive Technology, Shiyan, China, 442002
Jie Qian
School of Economics and Management, Hubei University of Automotive Technology, Shiyan, China, 442002

ABSTRACT

This work develops a novel approach for multicriteria group decision-making (MCGDM) problems based on the Choquet integral with simplified neutrosophic information. In such an environment, the truth-membership, indeterminacy-membership, and falsity-membership degrees for each element are singleton subsets in [0, 1]. In this paper, considering the fact that the Einstein t-norms and t-conorms can manage the relation between the computed objectives, the Einstein operations of simplified neutrosophic numbers (SNNs) are defined. Then, three definitions for the distance of SNNs are presented. Subsequently, taking advantage of the Choquet integral and that it can reflect the correlation of objectives, two aggregation operators for SNNs are also defined: specifically, the simplified neutrosophic Choquet integral weighted averaging operator and the simplified neutrosophic Choquet integral weighted geometric operator. Also, the properties related to these two aggregation operators are discussed in detail. Additionally, based on the aggregation operators and the technique for order preference by similarity to ideal solution (TOPSIS), a novel approach is developed to resolve MCGDM problems based on SNNs and unknown weight information, which has not been extensively discussed in the existing literature. Finally, this work provides a practical example to illustrate the practicality and effectiveness of the proposed approach; a comparison analysis is also presented based on the same example.