Multi-criteria decision-making based on hesitant fuzzy linguistic term sets: An outranking approach

2015 ◽  
Vol 86 ◽  
pp. 224-236 ◽  
Author(s):  
Jing Wang ◽  
Jian-qiang Wang ◽  
Hong-yu Zhang ◽  
Xiao-hong Chen
2020 ◽  
Vol 23 (4) ◽  
pp. 119-136
Author(s):  
Huchang Liao ◽  
Ruxue Ren ◽  
Jurgita Antucheviciene ◽  
Jonas Šaparauskas ◽  
Abdullah Al-Barakati

Within the context of resource constraints and ecological environment imbalance, the adoption of green suppliers can help construction enterprises achieve sustainable development and improve their competitiveness. The selection of sustainable construction suppliers is a multi-criteria decision-making problem since multiple factors should be considered. The increasingly complex decision-making environment makes it difficult for evaluators to give accurate evaluation values. In this regard, the hesitant fuzzy linguistic term set is a qualitative evaluation tool to represent the comprehensive linguistic evaluation values of experts by considering the hesitancy behaviors of experts. In this paper, a scientific multi-criteria decision-making model based on the improved Stepwise Weight Assessment Ratio Analysis (SWARA) method and the double normalization-based multi-aggregation (DNMA) method in the hesitant fuzzy linguistic environment is proposed. A new distance measure is proposed to measure the differences between hesitant fuzzy linguistic term sets with different lengths without changing the original evaluation information of experts. The proposed distance measure is applied to the proposed multi-criteria decision-making model. After improving the calculation steps of the traditional SWARA method, we can determine the weights of criteria effectively through our proposed model. To verify the applicability of the proposed method, we implement it to select sustainable building suppliers. The effectiveness of the method is verified by sensitivity analysis. We also compare the results obtained by our method and those derived by the Weight Aggregated Sum Product ASsessment (WASPAS) method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. The proposed method have a strong applicability to solve the sustainability-related decision problems given that it can effectively determine the weights of criteria and flexibly meet the needs of decision-makers by adjusting the coefficient.


Author(s):  
Na Zhao ◽  
Zeshui Xu ◽  
Zhiliang Ren

The purpose of this paper is to investigate the methods of constructing distance measures for hesitant fuzzy linguistic term sets (HFLTSs) and their applications in multi-criteria decision-making (MCDM). We first present some methods to construct distance measures for HFLTSs. Then, we discuss the properties of different distance measures in detail, which are very helpful in comparison of these distance measures for HFLTSs. After that, based upon the distance measures for HFLTSs, a decision-making method is proposed to solve the MCDM problems, in which the assessment values of alternatives over criteria are HFLTSs and the weights of criteria are completely unknown or expressed by HFLTSs. Finally, an example concerning the evaluation of movie quality is provided to demonstrate the practicability of the proposed method, and necessary comparative analyses are conducted to illustrate the effectiveness and advantages of the developed distance measures and the proposed decision-making method.


2022 ◽  
Vol 11 (1) ◽  
pp. 0-0

Motivated by the structural aspect of the probabilistic entropy, the concept of fuzzy entropy enabled the researchers to investigate the uncertainty due to vague information. Fuzzy entropy measures the ambiguity/vagueness entailed in a fuzzy set. Hesitant fuzzy entropy and hesitant fuzzy linguistic term set based entropy presents a more comprehensive evaluation of vague information. In the vague situations of multiple-criteria decision-making, entropy measure is utilized to compute the objective weights of attributes. The weights obtained due to entropy measures are not reasonable in all the situations. To model such situation, a knowledge measure is very significant, which is a structural dual to entropy. A fuzzy knowledge measure determines the level of precision in a fuzzy set. This article introduces the concept of a knowledge measure for hesitant fuzzy linguistic term sets (HFLTS) and show how it may be derived from HFLTS distance measures. Authors also investigate its application in determining the weights of criteria in multi-criteria decision-making (MCDM).


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