Multiattribute decision making based on Shannon's information entropy, non-linear programming methodology, and interval-valued intuitionistic fuzzy values

In this paper, we propose a novel multiattribute decision making (MADM) methodology based on Shannon's information entropy, the non-linear programming (NLP) methodology and interval-valued intuitionistic fuzzy values (IVIFVs), where attributes' weights and evaluating attributes' values with respect to alternatives are expressed by IVIFVs. Several examples are used to illustrate that the proposed MADM methodology can conquer the drawbacks of Wang and Chen's MADM methodology (2018) in interval-valued intuitionistic fuzzy (IVIF) environments. (C) 2018 Elsevier Inc. All rights reserved.