Some q-rung orthopair fuzzy Heronian mean operators in multiple attribute decision making

2018 ◽  
Vol 33 (7) ◽  
pp. 1426-1458 ◽  
Author(s):  
Guiwu Wei ◽  
Hui Gao ◽  
Yu Wei
2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaodi Liu ◽  
Jianjun Zhu ◽  
Guodong Liu ◽  
Jingjing Hao

The Heronian mean is a useful aggregation operator which can capture the interrelationship of the input arguments. In this paper, we develop some Heronian means based on uncertain linguistic variables, such as the generalized uncertain linguistic Heronian mean (GULHM) and uncertain linguistic geometric Heronian mean (ULGHM), and some of their desirable properties are also investigated. Considering the different importance of the input arguments, we define the generalized uncertain linguistic weighted Heronian mean (GULWHM) and uncertain linguistic weighted geometric Heronian mean (ULWGHM). Then, a method of multiple attribute decision making under uncertain linguistic environment is presented based on the GULWHM or the ULWGHM. In the end, an example is given to demonstrate the effectiveness and feasibility of the proposed method.


2018 ◽  
Vol 2018 ◽  
pp. 1-25 ◽  
Author(s):  
Bing Han ◽  
Huayou Chen ◽  
Jiaming Zhu ◽  
Jinpei Liu

This paper proposes an approach to linguistic multiple attribute decision-making problems with interactive unbalanced linguistic assessment information by unbalanced linguistic generalized Heronian mean aggregation operators. First, some generalized Heronian mean aggregation operators with unbalanced linguistic information are proposed, involving the unbalanced linguistic generalized arithmetic Heronian mean operator and the unbalanced linguistic generalized geometric Heronian mean operator. For the situation that the input arguments have different degrees of importance, the unbalanced linguistic generalized weighted arithmetic Heronian mean operator and the unbalanced linguistic generalized weighted geometric Heronian mean operator are developed. Then we investigate their properties and some particular cases. Finally, the effectiveness and universality of the developed approach are illustrated by a low-carbon tourist instance and comparison analysis. A sensitivity analysis is performed as well to test the robustness of proposed methods.


Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1191
Author(s):  
Ximei Hu ◽  
Shuxia Yang ◽  
Ya-Ru Zhu

In actual multiple attribute decision making, people often use language to evaluate attributes of the object, and sometimes there are associations between the attributes. Therefore, the study of multiple attribute decision making with language as attributes and associations between attributes is of great theoretical significance and practical value. The Heronian mean is not only an operator which reflects the associations between attributes, but also has excellent properties, including idempotency, monotonicity, boundedness, parameter symmetry, and alternate symmetry. In this paper, firstly a new linguistic generalized weighted Heronian mean (LGWHM) was provided, and its properties including idempotency, monotonicity, boundedness, and limit were studied. Then, a new three-parameter linguistic generalized weighted Heronian mean (TPLGWHM) and its idempotency, monotonicity, and boundedness properties were proposed. Finally, multi-attribute decision making methods based on the new linguistic generalized weighted Heronian mean were given, and an example was analyzed and compared with other methods.


2018 ◽  
Vol 2018 ◽  
pp. 1-24
Author(s):  
Bing Han ◽  
Zhifu Tao ◽  
Huayou Chen ◽  
Ligang Zhou

In many countries, green products play a critical role in energy recycling and environment protection. The selection of green products can be regarded as a multiple attribute decision making (MADM) problem. Due to the complexity and uncertainty of the problem, decision makers may give their personal preference values to different attributes of alternatives by intuitionistic unbalanced linguistic term sets. The main purpose of this paper is to put forward a new generalized multiple attribute group decision making (GMAGDM) approach based on the intuitionistic unbalanced linguistic dependent weighted generalized Heronian mean (IULDWGHM) operator and the intuitionistic unbalanced linguistic dependent weighted generalized geometric Heronian mean (IULDWGGHM) operator. The proposed method can not only relieve the influence of unfair assessments, but also consider the interaction effects of attributes. Furthermore, the appropriate parameter values and operators can be selected to meet the different risk preference of decision makers and actual requirements. Finally, a green products selection case is given to illustrate the effectiveness and universality of the developed approach.


Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1363
Author(s):  
Ximei Hu ◽  
Shuxia Yang ◽  
Ya-Ru Zhu

For the aggregation problem of attributes with a correlation relationship, it is often necessary to take the correlation factor into account in order to make the decision results more objective and reasonable. The Heronian mean is an aggregation operator which reflects the interaction between attributes. It is of great theoretical and practical significance to study and popularize the multiple attribute decision-making methods based on the Heronian mean operator. In this paper, we first give a new three-parameter generalized weighted Heronian mean (TPGWHM), which has a series of excellent properties such as idempotency, monotonicity and boundedness. At the same time, the relationship between the TPGWHM and the existing aggregation operators is given. Then, we propose the intuitionistic fuzzy three-parameter generalized weighted Heronian mean (IFTPGWHM) and give its idempotency, monotonicity, boundedness and limit properties. On this basis, a multiple attribute decision-making method based on the TPGWHM and a multiple attribute decision-making method based on the IFTPGWHM are given, and corresponding examples are given and analyzed.


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