Interval-valued intuitionistic fuzzy envelopment analysis and preference fusion. (April 2020)

• Record Type: Journal Article
• Authors: Zhou, Wei; Chen, Jin; Ding, Bingqing; Meng, Sun
• Is Part Of: Computers & industrial engineering. Volume 142(2020)
• Publication Date: 2020-04
• Subjects: Envelopment analysis -- Interval-valued intuitionist fuzzy set -- Qualitative evaluation -- Preference fusion -- Alternative development; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2020.106361
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: The interval-valued intuitionistic fuzzy envelopment analysis (IIFEA) is proposed. Two IIFEA models are proposed from the perspectives of non-membership and membership. The IIFEA model is further developed by fusing the DM's preference for attributes. The alterative development method is designed to enhance the "bad" alternatives. These methods are shown by an example of selecting and enhancing the alternatives. Abstract: The interval-valued intuitionistic fuzzy set (IIFS) is an effective tool to describe qualitative evaluations using two interval values from two perspectives of "good" and "bad". In this study, a new decision-making method based on the envelopment efficiency of IIFS is proposed, which can be introduced to select the optimal alternative and improve the inefficient ones. To do this, we firstly propose the ratio comparison rules of IIFS, based on which the interval-valued intuitionistic fuzzy envelopment analysis (IIFEA) is demonstrated. After that, we develop the IIFEA-N and IIFEA-M models on the basis of non-membership and membership. Their dual forms are derived so that the IIFEA-N and IIFEA-M models can be transformed into linear programming, which are calculable. With respect to the attributes' difference, we further construct the preference IIFEA (PIIFEA) model by fusing subjective preference rather than quantitative weights. Therefore, the optimal alternative can be selected based on the decision makers' preference, and the development approaches also can be given to the inefficient alternatives. Subsequently, a complete decision-making process is provided. At last, an example for the CEO of an international hotel to select a GM of the biggest branch in China is illustrated to show the effectiveness of the proposed methods.