Interval-valued intuitionistic fuzzy envelopment analysis and preference fusion

Zhou, Wei; Chen, Jin; Ding, Bingqing; Meng, Sun

doi:10.1016/j.cie.2020.106361

Cited by 6 publications

(4 citation statements)

References 41 publications

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“…59 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: Studies On Envelopment Analysismentioning

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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Section: Studies On Envelopment Analysismentioning

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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“…Che et al [48] constructed a new entropy measure in the context of IVIFS by introducing the proposed distance function. Zhou et al [49] raised the ratio comparison rules of IVIFS. Bustince et al [50] introduced some new similarity measures between interval-valued intuitionistic fuzzy numbers (IVIFNs) considering the width of intervals and admissible orders.…”

Section: Introductionmentioning

confidence: 99%

Cybersecurity Risk Assessment of Industrial Control Systems Based on Order-α Divergence Measures Under an Interval-Valued Intuitionistic Fuzzy Environment

Guo

Ding

2022

IEEE Access

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With the increasing deployment of network technologies in industrial control systems (ICSs), cybersecurity has become a challenge in ICSs. Cybersecurity risk assessment (CRA) plays an important role in cybersecurity protection of ICSs. However, the weights of risk indices are constants in traditional CRA methods, and they do not fully consider the requirements of risk identification. In this paper, we define a novel order-α divergence measure for interval-valued intuitionistic fuzzy numbers (IVIFNs) and further develop a novel CRA approach for ICSs based on the proposed divergence measure under an interval-valued intuitionistic fuzzy environment to contribute to the research gap. First, an order-α divergence measure for IVIFNs is defined considering flexibility and robustness of divergence measures with the parameter. Next, a variable weight-based CRA approach for ICSs is developed. In this approach, IVIFNs are adopted to describe evaluation values of risk indices. The weights of risk indices are variable weight vectors and they are determined by the relative divergence closeness. Integration approaches of each node and each attack path in attack-defense trees (ADTs) are proposed based on the operations of IVIFNs, and risk scores of each attack path are calculated by using the score function. Finally, we apply the proposed method to the CRA of a civil aviation fuel supply automatic control system and verify its effectiveness and advantages by comparing it with other methods. This method can dynamically adjust the weights of risk indices considering the relationship between each risk index and the highest risk, and therefore, it can more effectively recognize the highest risk of ICSs than the traditional CRA method. In addition, it can also match the risk attitude of decision-makers by adjusting the parameter α.INDEX TERMS Industrial control systems (ICSs), cybersecurity risk assessment (CRA), order-αdivergence measure, interval-valued intuitionistic fuzzy numbers (IVIFNs), variable weight vectors.

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“…In the DEA literature, there are also some models of DEA with IFSs, see [52][53][54][55][56][57][58][59][60]. However, in actual activities, there are some indeterminate information.…”

Section: Introductionmentioning

confidence: 99%

A Neutrosophic-Based Approach in Data Envelopment Analysis with Undesirable Outputs

Mao

Guo

Fallah

et al. 2020

Mathematical Problems in Engineering

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Data Envelopment Analysis is one of the paramount mathematical methods to compute the general performance of organizations, which utilizes similar sources to produce similar outputs. Original DEA schemes involve crisp information of inputs and outputs that may not always be accessible in real-world applications. Nevertheless, in some cases, the values of the data are information with indeterminacy, impreciseness, vagueness, inconsistent, and incompleteness. Furthermore, the conventional DEA models have been originally formulated solely for desirable outputs. However, undesirable outputs may additionally be present in the manufacturing system, which wishes to be minimized. To tackle the mentioned issues and in order to obtain a reliable measurement that keeps original advantage of DEA and considers the influence of undesirable factors under the indeterminate environments, this paper presents a neutrosophic DEA model with undesirable outputs. The recommended technique is based on the aggregation operator and has a simple construction. Finally, an example is given to illustrate the new model and ranking approach in details.

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Interval-valued intuitionistic fuzzy envelopment analysis and preference fusion

Cited by 6 publications

References 41 publications

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

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

Cybersecurity Risk Assessment of Industrial Control Systems Based on Order-α Divergence Measures Under an Interval-Valued Intuitionistic Fuzzy Environment

A Neutrosophic-Based Approach in Data Envelopment Analysis with Undesirable Outputs

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