Bidirectional projection measure of linguistic neutrosophic numbers and their application to multi-criteria group decision making. (February 2019)

• Record Type: Journal Article
• Authors: Liu, Peide; You, Xinli
• Is Part Of: Computers & industrial engineering. Volume 128(2019)
• Page Start: 447
• Page End: 457
• Publication Date: 2019-02
• Subjects: Linguistic neutrosophic numbers -- Bidirectional projection measure -- Distance measure -- SHAPLEY weight -- MCGDM; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2018.12.052
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Define a new distance measures between two linguistic neutrosophic numbers (LNNs). Build a model based on the maximum deviation to obtain fuzzy measure. Obtain the objective weight vector of evaluation criteria. Put forward to the bidirectional projection measure with LNNs. Develop a novel MAGDM method based on the bidirectional projection. Abstract: Linguistic neutrosophic numbers (LNNs) are an effective tool in describing the incomplete and indeterminate evaluation information by using three linguistic variables (LVs) to denote the truth-degree (TD), indeterminacy-degree (ID), and falsity-degree (FD), and the bidirectional projection measure has some advantages in dealing with multi-criteria group decision making (MCGDM) problems because it can consider both the distance and the included angle, but more importantly, it considers the bidirectional projection between each alternative and the ideal solution. In this paper, we define a new distance measure between two linguistic neutrosophic sets (LNSs), and build a model based on the maximum deviation to obtain fuzzy measure, further, we develop the bidirectional projection-based MCGDM method with LNNs in which a weight model based on fuzzy measure is proposed where the weights of evaluation criteria is partial unknown and the interactions among criteria are considered. Finally, we use some examples to verify the effectiveness of the proposed approach and demonstrate its advantages by comparing with some existing methods.