Intertemporal Hesitant Fuzzy Soft Sets: Application to Group Decision Making

Liu, Yaya; Alcantud, José Carlos R.; Rodríguez, Rosa M.; Qin, Keyun; Martínez, Luis

doi:10.1007/s40815-020-00798-w

Cited by 18 publications

(10 citation statements)

References 47 publications

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“…Hesitant fuzzy linguistic term sets are mainly considered to obtain the evaluations of the decision makers under the hesitancy [24]. In this framework, membership function can be created based on the preferences of these people.…”

Section: A Proposed Methodsmentioning

confidence: 99%

“…For this purpose, in many different studies, this evaluation has been conducted under the hesitancy. The main advantage of this issue is that uncertainty can be minimized when expert team could not reach a consensus [24,25]. The α-cut operation on the fuzzy set is defined for categorizing the crisp sets into subsets with membership function values greater than or equal to alpha for one specific purpose [26].…”

Section: Introductionmentioning

confidence: 99%

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Analyzing the Investments Strategies for Renewable Energies Based on Multi-Criteria Decision Model

Zhong

Yüksel

et al. 2020

IEEE Access

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The purpose of this study is to determine appropriate innovative strategies for the renewable energy investments. For this purpose, a hybrid multi-criteria decision-making (MCDM) model is proposed based on interval type-2 (IT2) fuzzy sets and alpha cut levels. Within this context, hesitant IT2 fuzzy DEMATEL-Based Analytic Network Process (DANP) with alpha cut levels is applied for weighting the customer requirements. Moreover, hesitant IT2 fuzzy technique for order preference by similarity to ideal solution (TOPSIS) with alpha cut levels is used for ranking the TRIZ-based strategies priorities of renewable energy investments based on house of quality technique. These strategies are also ranked with hesitant IT2 fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) approach to make a comparative evaluation. The results illustrate that ease of access and security are among the most prominent factors of customer requirements for renewable energy investments. It is also identified that innovative technical requirement entitled cushion in advance has the best choice for the sustainable renewable energy projects. Furthermore, the results of proposed model using hesitant IT2 fuzzy DANP and hesitant IT2 fuzzy TOPSIS are identical for the different levels of alpha cut. In addition, it is also defined that the results of hesitant IT2 fuzzy TOPSIS and hesitant IT2 fuzzy VIKOR are quite coherent. This is a clear evidence that the proposed model is coherent and could provide comprehensive results for the future studies. It is strongly recommended that a detailed analysis is required to identify the risks in renewable energy investment projects. Hence, necessary actions can be taken appropriately so that it can be possible to prevent problems before they grow.

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Section: A Proposed Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analyzing the Investments Strategies for Renewable Energies Based on Multi-Criteria Decision Model

Zhong

Yüksel

et al. 2020

IEEE Access

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“…Lin et al [30] proposed a new probability density based ordered weighted averaging (PDOWA) operator and demonstrated its application for the assessment of smart phones. Liu et al [31,32] introduced hybrid models of long-term intertemporal hesitant fuzzy soft sets (LIT-HFSS) and hesitant linguistic expression soft sets (HLESS) along with significant group DM algorithms. Rodríguez et al [39] proposed the comprehensive minimum cost models based on both distance measure and consensus degree to address the consistent fuzzy preference relations.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Decision-Making Approach Under Complex Pythagorean Fuzzy N-Soft Sets

Akram¹,

Wasim²,

Al-Kenani³

2021

IJCIS

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The main objectives of this article include the formal statement of a new mathematical model of uncertain knowledge and the presentation of its potential applications. The novel hybrid model is called complex Pythagorean fuzzy N-soft set (CPFNSS) because it enjoys both the parametric structure of N-soft sets and the most prominent features of complex Pythagorean fuzzy sets in order to capture the nuances of two-dimensional inexact information. We demonstrate that this model serves as a competent tool for ranking-based modeling of parameterized fuzzy data. We propose some basic set-theoretical operations on CPFNSSs and explore some of their practical properties. Furthermore, we elaborate the Einstein and algebraic operations on complex Pythagorean fuzzy N-soft values (CPFNSVs). We interpret its relationships with contemporary theories to vindicate the versatility of the proposed model. Moreover, we develop three algorithms to unfold the application of proposed theory in multi-criteria decision-making (MCDM). Some illustrative applications give a practical justification for these strategies. Finally, we conduct a comparative analysis of the performance of these algorithms with existing MCDM techniques, namely, choice values and Dchoice values of Pythagorean fuzzy N-soft set (PFNSS), which validates the effectiveness of the proposed techniques.

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“…Chen [15] proposed a score function and accuracy function to rank DHFE based on average value of DHFE, while Ren et al [16] suggested that the score feature relies on three aspects: (1) the hesitant degree of membership and non-membership functions; (2) the mean hesitant degree of DHFE arising from one minus mean membership and non-membership values; (3) the non-membership feature should be deemed more significant. Numerous researchers applied the score functions of HFS and DHFS in their research [17], [18], [27]- [29], [19]- [26]. While many excellent contributions to score functions of varying types were made in the sense of DHFS, certain critical issues remain to be tackled.…”

Section: Introductionmentioning

confidence: 99%

Z-Score Functions of Dual Hesitant Fuzzy Set and Its Applications in Multi-Criteria Decision Making

Rodzi¹,

Ahmad²,

Ismail³

et al. 2021

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Dual hesitant fuzzy set (DHFS) consists of two parts: membership hesitant function and non-membership hesitant function. This set supports more exemplary and flexible access to set degrees for each element in the domain and can address two types of hesitant in this situation. It can be considered a powerful tool for expressing uncertain information in the decision-making process. The function of z-score, namely z-arithmetic mean, z-geometric mean, and z-harmonic mean, has been proposed with five important bases, these bases are hesitant degree for dual hesitant fuzzy element (DHFE), DHFE deviation degree, parameter , (the importance of the hesitant degree), parameter  , (the importance of the deviation degree) and parameter , (the importance of membership (positive view) or non-membership (negative view). A comparison of the z-score with the existing score function was made to show some of their drawbacks. Next, the z-score function is then applied to solve multi-criteria decision making (MCDM) problems. To illustrate the proposed method's effectiveness, an example of MCDM specifically in pattern recognition has been shown.

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Intertemporal Hesitant Fuzzy Soft Sets: Application to Group Decision Making

Cited by 18 publications

References 47 publications

Analyzing the Investments Strategies for Renewable Energies Based on Multi-Criteria Decision Model

Analyzing the Investments Strategies for Renewable Energies Based on Multi-Criteria Decision Model

A Hybrid Decision-Making Approach Under Complex Pythagorean Fuzzy N-Soft Sets

Z-Score Functions of Dual Hesitant Fuzzy Set and Its Applications in Multi-Criteria Decision Making

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