Multiattribute decision making based on entropy under interval-valued intuitionistic fuzzy environment
type: Item
instance of: scholarly article
title: Multiattribute decision making based on entropy under interval-valued intuitionistic fuzzy environment
zbMATH Open document ID: 1296.91092
author: Yingjun Zhang
author: Peihua Li
author: Yizhi Wang
author: Peijun Ma
author: Xiaohong Su
published in: Mathematical Problems in Engineering
publication date: 2014-10-13T00:00:00Z
review text: Summary: Multiattribute decision making (MADM) is one of the central problems in artificial intelligence, specifically in management fields. In most cases, this problem arises from uncertainty both in the data derived from the decision maker and the actions performed in the environment. Fuzzy set and high-order fuzzy sets were proven to be effective approaches in solving decision-making problems with uncertainty. Therefore, in this paper, we investigate the MADM problem with completely unknown attribute weights in the framework of interval-valued intuitionistic fuzzy (IVIF) set (IVIFS). We first propose a new definition of IVIF entropy and some calculation methods for IVIF entropy. Furthermore, we propose an entropy-based decision-making method to solve IVIF MADM problems with completely unknown attribute weights. Particular emphasis is put on assessing the attribute weights based on IVIF entropy. Instead of the traditional methods, which use divergence among attributes or the probabilistic discrimination of attributes to obtain attribute weights, we utilize the IVIF entropy to assess the attribute weights based on the credibility of the decision-making matrix for solving the problem. Finally, a supplier selection example is given to demonstrate the feasibility and validity of the proposed MADM method.
Mathematics Subject Classification ID: 91B06
Mathematics Subject Classification ID: 68T37
Mathematics Subject Classification ID: 90B50
Mathematics Subject Classification ID: 90C70
zbMATH DE Number: 6354351
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 6354351