Multiplicative Consistency Adjustment Model and Data Envelopment Analysis-Driven Decision-Making Process with Probabilistic Hesitant Fuzzy Preference Relations

Jin, Feifei; Garg, Harish; Pei, Lidan; Liu, Jinpei; Chen, Huayou

doi:10.1007/s40815-020-00944-4

Cited by 48 publications

(29 citation statements)

References 40 publications

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“…Thus, we conclude that the proposed methodology can effectively capture the uncertain information and guarantees robustness. In future, the outcome of this article may be extended to a number of other real-life problems such as supplier selection, recognition of patterns, and allocation of resources [39][40][41][42][43][44][45].…”

Section: Discussionmentioning

confidence: 99%

Algorithm for solving the decision-making problems based on correlation coefficients under cubic intuitionistic fuzzy information: a case study in watershed hydrological system

Garg

Kaur

2021

Complex Intell. Syst.

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Cubic intuitionistic fuzzy sets (CIFSs) are a powerful and relevant medium for expressing imprecise information to solve the decision-making problems. The conspicuous feature of their mathematical concept is that it considers simultaneously the hallmarks of both the intuitionistic fuzzy sets (IFSs) and interval-valued IFSs. The present paper is divided into two parts: (i) defining the correlation measures for the CIFSs; (ii) introducing the decision-making algorithm for the CIFS information. Furthermore, few of the fundamental properties of these measures are examined in detail. Based on this, we define a novel algorithm to solve the multi-criteria decision-making process and illustrate numerical examples related to watershed’s hydrological geographical areas, global recruitment problem and so on. A contrastive analysis with several existing studies is also administered to test the effectiveness and verify the proposed method.

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Section: Discussionmentioning

confidence: 99%

Algorithm for solving the decision-making problems based on correlation coefficients under cubic intuitionistic fuzzy information: a case study in watershed hydrological system

Garg

Kaur

2021

Complex Intell. Syst.

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“…Zhou et al also extended these two models to process interval-valued intuitionistic fuzzy sets 63 and hesitant fuzzy sets. 64,65 However, HFLTSs show different information structures from the intuitionistic fuzzy set, interval-valued intuitionistic fuzzy set, and hesitant fuzzy set. These models cannot be directly used for processing HFLTSs.…”

Section: Studies On Envelopment Analysismentioning

confidence: 99%

“…These two models are proposed based on the ratio of the membership to the nonmembership and they also provide the suggestions for improving nonoptimal alternatives. Zhou et al also extended these two models to process interval‐valued intuitionistic fuzzy sets 63 and hesitant fuzzy sets 64,65 . However, HFLTSs show different information structures from the intuitionistic fuzzy set, interval‐valued intuitionistic fuzzy set, and hesitant fuzzy set.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

Lin

Chen

et al. 2021

Int J Intell Syst

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Evaluating startup companies is an important management process for technology business incubators and it is also a typical multicriteria decision‐making (MCDM) problem. There exist various methods that have proposed to solve MCDM problems, but these methods heavily depend on the exact criteria weight values. The decision results of these methods are unstable. Moreover, they cannot provide the improvement suggestions for the nonoptimal startup companies. To overcome these two drawbacks, we propose a novel hesitant fuzzy linguistic decision‐making method to solve the problem of evaluating startup companies. To this end, a novel semantic comparison method based on the experts' psychology and the ratio of score value to deviation degree is proposed to compare the hesitant fuzzy linguistic term sets. Then, a novel definition of hesitant fuzzy linguistic information envelopment efficiency (HFLIEE) is proposed, based on which, a novel hesitant fuzzy linguistic information envelopment analysis (HFLIEA) model and a novel preference model are proposed. By solving these models, all the alternatives can be ranked and nonoptimal alternatives can be improved. Finally, the numerical analysis is given to illustrate the applicability of the proposed models and the robustness analyses of the proposed models are provided. At the same time, they are compared with the previous hesitant fuzzy linguistic decision‐making methods.

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“…. (26) where w i denotes the important degree of p i , and it satisfies that w i ≥ 0 and n ∑ i=1 w i = 1. 1, 2, . .…”

Section: Definition 10 Let P I (I =mentioning

confidence: 99%

“…Considering the importance of the correlation coefficient in data analysis, Song et al [22] introduced a couple of new correlation coefficient expressions to measure the nexus between the PHFSs. Moreover, some of the researches have applied probability to linguistic term sets [23,24] and preference relations [25,26].…”

Section: Introductionmentioning

confidence: 99%

Investment Selection Based on Bonferroni Mean under Generalized Probabilistic Hesitant Fuzzy Environments

Jin

et al. 2021

Mathematics

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In investment selection problems, the existence of contingency and uncertainty may result in the loss of attribute information. Then, how to make proper investment decision-making will be a tricky proposition. In this work, a multiattribute group decision making (MAGDM) method based on the generalized probabilistic hesitant fuzzy Bonferroni mean (GPHFBM) operator is constructed, which enables decision-makers to select the proper parameters in decision-making process. Firstly, the GPHFBM operator is proposed by combining the Bonferroni mean operator and Archimedean norm. Secondly, five excellent properties of the GPHFBM operator are discussed in detail. In view of applications, we further develop some special aggregation operators for GPHFBM with the various values of parameters b, d and additive operators g(t). Finally, we propose a probabilistic hesitant fuzzy MAGDM method based on the GPHFBM operator to analyze the aggregated information. A case study of the investment of social insurance funds is given to depict the validity and reasonability of the proposed method. Ultimately, the company X4 is selected as the investment company with the best comprehensive indicator.

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Multiplicative Consistency Adjustment Model and Data Envelopment Analysis-Driven Decision-Making Process with Probabilistic Hesitant Fuzzy Preference Relations

Cited by 48 publications

References 40 publications

Algorithm for solving the decision-making problems based on correlation coefficients under cubic intuitionistic fuzzy information: a case study in watershed hydrological system

Algorithm for solving the decision-making problems based on correlation coefficients under cubic intuitionistic fuzzy information: a case study in watershed hydrological system

Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

Investment Selection Based on Bonferroni Mean under Generalized Probabilistic Hesitant Fuzzy Environments

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