Information-Theoretic-Entropy Based Weight Aggregation Method in Multiple-Attribute Group Decision-Making

Abstract

Weight aggregation is the key process to solve a multiple-attribute group decision-making (MAGDM) problem. This paper is trying to propose a possible approach to objectivize subjective information and to aggregate information from attribute values themselves and decision-makers' judgment. An MAGDM problem without information about decision-makers' and attributes' weight is considered. In order to define decision-makers' subjective preference, their utility function is introduced. The attributes value matrix is converted into a subjective attributes value matrix based on their subjective judgment on attribute values. By utilizing the entropy weighting technique, decision-maker's subjective weight on attributes and objective weight on attributes are determined individually based on the subjective attributes value matrix and attributes value matrix. Based on the principle of minimum cross-entropy, all decision-makers' subjective weights are integrated into a single weight vector that is closest to all decision-makers' judgment without any extra information added. Then, by applying the principle of minimum cross-entropy again, a weight aggregation method is proposed to combine the subjective and objective weight of attributes. Finally, an MAGDM example of project choosing is presented to illustrate the procedure of the proposed method.

Crane Safety Assessment Method Based on Entropy and Cumulative Prospect Theory

“…The VS assessment method avoids some of the limitations of MMP that may result in unreasonable assessments [34,48]. According to VS, the grade characteristic value H [49] of a sample can be calculated as:…”

“…In contrast, if an attribute possesses lower information entropy with a higher variation in attribute value, it should have a higher weight. Entropy has become an effective method for determining the objective weights [31][32][33][34]. Chen et al [35] used entropy to calculate the objective weights in a risk index for a tower crane, and Wang et al [36] determined the objective weights of water quality metrics in Meiliang Bay (part of Lake Taihu, China) by using an entropy-based method.…”

A Novel Centrality of Influential Nodes Identification in Complex Networks

“…There are many methods to compute the weights, such as Analytic Hierarchy Process (AHP) method, Delphi method, principle element analysis and entropy technology [38]- [40]. Here, we choose entropy technology to calculate the weights of I D (i) and I C (i) for its excellent performance [41]. The process of entropy technology is represented as follows.…”

Constructing a Measurement Method of Differences in Group Preferences Based on Relative Entropy

“…Makowski et al [22] studied the issue of transitivity of preferences in an argument between two people. A recent study, "Information-Theoretic-Entropy Based Weight Aggregation Method in Multiple-Attribute Group Decision-Making" from He et al [23] is also a study of decision makers' preferences. Thus, studying individual preferences in the decision-making process using relative entropy theory is more common than studying group preferences.…”