An algorithmic-based multi-attribute decision making model under intuitionistic fuzzy environment

2021 ◽  
pp. 1-15
Author(s):  
Eshika Aggarwal ◽  
B.K. Mohanty
Keyword(s):  
Decision Making ◽  
Confidence Level ◽  
Decision Aid ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Multi Attribute Decision Making ◽  
Product Assessment ◽  
Decision Making Model ◽  
Product Rating ◽  
Interval Valued

An outranking procedure for Multi-Attribute Decision-Making (MADM) problems is introduced in our work that acts as a decision-aid in recommending the products to the buyers. The buyer’s product assessment is taken as Interval-Valued Intuitionistic Fuzzy Sets (IVIFS) in each attribute. The confidence level that is implicit in the buyer’s product rating is explicated in the proposed work using fuzzy entropy. As the confidence level of the buyer on the product assessment is for both satisfaction and reluctance, it is suitably distributed in membership and non-membership parts of IVIFS. Our work generates a dominance matrix that represents partial or full dominance of one product over another after scoring the products that are unified with buyer’s confidence. The proposed work suggests the product ranking after ascertaining the buyer’s flexibility. An algorithm is written in our work to validate the procedure developed. We have compared our work with other similar works to highlight the benefits of the proposed work. A numerical example is illustrated to highlight the procedure developed.

scholarly journals Heronian Means as Aggregation Operators for Multi-Attribute Decision Making Applications

2018 ◽  
Author(s):  
Xiaopu Shang ◽  
Jun Wang ◽  
Anupam Nanda ◽  
Weizi Li
Keyword(s):  
Decision Making ◽  
Aggregation Operators ◽  
Pythagorean Fuzzy Set ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Novel Approach ◽  
Multi Attribute Decision Making ◽  
Interval Valued ◽  
Heronian Mean

The Pythagorean fuzzy set (PFS), which is characterized by a membership and a non-membership degree and the square sum of them is less or equal to one, can act as an effective tool to express decision makers’ fuzziness and uncertainty. Considering that the Heronian mean (HM) is a powerful aggregation operator which can take the interrelationship between any two arguments, we study the HM in Pythagorean fuzzy environment and propose new operators for aggregating interval-valued Pythagorean fuzzy information. First, we investigate the HM and geometric HM (GHM) under interval-valued intuitionistic fuzzy environment and develop a series of aggregation operators for interval-valued intuitionistic fuzzy numbers (IVIFNs) including interval-valued intuitionistic fuzzy Heronian mean (IVIFHM), interval-valued intuitionistic fuzzy geometric Heronian mean (IVIFGHM), interval-valued intuitionistic fuzzy weighted Heronian mean (IVIFWHM) and interval-valued intuitionistic fuzzy weighted geometric Heronian mean (IVIFWGHM). Second, some desirable and important properties of these aggregation operators are discussed. Third, based on these aggregation operators, a novel approach to multi-attribute decision making (MADM) is proposed. Finally, to demonstrate the validity of the approach, a numerical example is provided and discussed. Moreover, we discuss several real-world applications of these operators within policy-making contexts.

Multi-Attribute Decision Making Method Based on the Satisfaction under Interval-Valued Intuitionistic Fuzzy Environment

2014 ◽  
Vol 631-632 ◽  
pp. 1253-1256
Author(s):  
Mei Gui ◽  
Yue Lin Huang
Keyword(s):  
Decision Making ◽  
Ideal Point ◽  
Score Function ◽  
Weight Vector ◽  
Satisfaction Function ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Multi Attribute Decision Making ◽  
Interval Valued

In this paper, it discussed multi-attribute decision making (MADM) problems in which the information about attribute weights is incomplete and decision-making information is characterized by interval-valued intuitionistic fuzzy number (IVIFNs), decision-making method is proposed based on the satisfaction. First, we define positive and negative ideal point of the comprehensive attribute values and satisfaction function, and make use of satisfaction function to establish a multi-objective optimization model, apply this model to determine the attribute weight vector, calculate the comprehensive attribute values, rank the alternatives according to the score function and precise function of the comprehensive attribute values. Finally, the examples are given to show that the method is reasonable and effective.

Method of Multi-Attribute Decision Making for Interval-Valued Intuitionistic Fuzzy Sets Based on Mentality Function

2010 ◽  
Vol 44-47 ◽  
pp. 1075-1079
Author(s):  
Liang Zhong Shen ◽  
Guang Bo Li ◽  
Wen Bin Liu
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Intuitionistic Fuzzy Sets ◽  
Decision Makers ◽  
Ranking Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multi Attribute Decision Making ◽  
Decision Making Model ◽  
Interval Valued

This paper has summarized the current ranking method for interval-valued intuitionistic fuzzy numbers, and then through the introduction of decision-makers’ mentality indicator, presented a new ranking method for interval-valued intuitionistic fuzzy numbers based on mentality function. Not only the nature of mentality function is deeply discussed but also the decision-making model based on the interval-valued intuitionistic fuzzy numbers is constructed. At last, an example is illustrated to prove the model's accuracy and effectiveness.

scholarly journals The Interval-Valued Intuitionistic Fuzzy Optimized Weighted Bonferroni Means and Their Application

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Ya-ming Shi ◽  
Jian-min He
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Practical Case ◽  
Basic Properties ◽  
Bonferroni Mean ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Aggregation Techniques ◽  
Interval Valued

We investigate and propose two new Bonferroni means, that is, the optimized weighted BM (OWBM) and the generalized optimized weighted BM (GOWBM), whose characteristics are to reflect the preference and interrelationship of the aggregated arguments and can satisfy the basic properties of the aggregation techniques simultaneously. Further, we propose the interval-valued intuitionistic fuzzy optimized weighted Bonferroni mean (IIFOWBM) and the generalized interval-valued intuitionistic fuzzy optimized weighted Bonferroni mean (GIIFOWBM) and detailed study of their desirable properties such as idempotency, monotonicity, transformation, and boundary. Finally, based on IIFOWBM and GIIFOWBM, we give an approach to group decision making under the interval-valued intuitionistic fuzzy environment and utilize a practical case involving the assessment of a set of agroecological regions in Hubei Province, China, to illustrate the developed methods.

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