Fuzzy Soft Set Theory and Its Application in Group Decision Making

Sooraj, T. R.; Mohanty, Ramakanta; Tripathy, B. K.

doi:10.1007/978-981-10-1023-1_17

Cited by 20 publications

(3 citation statements)

References 12 publications

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“…Rokni et al [10] developed a new framework for optimizing shop scheduling using fuzzy set theory. Sooraj [11] proposed a new algorithm by applying the fuzzy soft set theory in group decision making. Dogan et al [12] proposed a fuzzy decision model combining analytic hierarchy process and technique for order of preference by similarity to ideal solution with intuitionistic fuzzy sets to locate autonomous vehicles.…”

Section: Introductionmentioning

confidence: 99%

Dam Safety Evaluation Based on Interval-Valued Intuitionistic Fuzzy Sets and Evidence Theory

Shu

Bao

et al. 2020

Sensors

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Considering the multi-sources, heterogeneity and complexity of dam safety assessment, a dam safety assessment model based on interval-valued intuitionistic fuzzy set and evidence theory is proposed to perform dam safety reliability evaluations. In the proposed model, the dynamic reliability based on the supporting degree is applied to modify the data from homologous information. The interval-valued intuitionistic fuzzy set is used to describing the uncertainty and fuzziness between heterogeneous information. Evidence theory is employed to integrate the data from heterogeneous information. Finally, a multiple-arch dam undergoing structural reinforcement is taken as an example. The evaluation result before reinforcement shows that the safety degree of the dam is low and the potential risk is more likely to be located at the dam section #13. From the geological survey before reinforcement, there exist weak fracture zone and broken mud belt in the foundation of the dam section #13. The comparison between the evaluation results before and after reinforcement indicates that the dam become safer and more stable after reinforcement.

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Section: Introductionmentioning

confidence: 99%

Dam Safety Evaluation Based on Interval-Valued Intuitionistic Fuzzy Sets and Evidence Theory

Shu

Bao

et al. 2020

Sensors

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“…Therefore, the establishment of a non-random process model for seismic loads based on small amounts of data is an effective complement to the random vibration method for investigating the response of pipelines with earthquakes. The application of fuzzy comprehensive evaluation model focuses on management science, safety assessment, risk assessment, and other fields [20]. In a fuzzy set, the degree of membership is used to describe the degree of comparison, which is better than the certain evaluation.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model

2019

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It is necessary to conduct a safety assessment for pipelines which are regarded as important lifeline projects after an earthquake. Since the random process of loading in earthquake engineering requires a large amount of samples, this paper establishes a non-random vibration method based on convex model theory and applies it to small sample engineering. Moreover, a space–time analytical model of buried pipeline and a finite element model are established to solve the dynamic response of pipelines with non-random process seismic excitation. Furthermore, the randomness of the stress values of the pipeline subjected to earthquake and the fuzziness of the degree of damage to pipelines are considered. Therefore, a novel method for assessing damage to pipelines is proposed based on cloud model. The results indicate that an analysis of non-random vibration combined with the cloud inference method can solve the fuzziness and randomness of the quantitative description and qualitative concept conversion for damage evaluation of pipelines. The method is also an adaptive and effective assessment method for pipelines exposed to earthquake and is able to promote safety management of pipeline engineering.

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“…Cagman and Karatas (2013) defined the intuitionistic fuzzy soft sets, followed by studies on generalised intuitionistic fuzzy soft sets (Agarwal et al, 2013;Khalil, 2015), multi Q-fuzzy parameterised soft sets (Adam and Hassan, 2014), possibility multi-fuzzy soft sets (Zhang and Shu, 2014;Khalil and Hassan, 2017b), bipolar fuzzy soft sets (Abdullah et al, 2014), trapezoidal interval type-2 fuzzy soft sets (Zhang and Zhang, 2013;Khalil and Hassan, 2017c) and vague soft set relations and functions (Alhazaymeh and Hassan, 2015). Since Zadeh (1965) introduced his model, fuzzy sets and fuzzy logic have been applied to many real life problems in uncertain, ambiguous environment (Alhazaymeh and Hassan, 2012c;Singh et al, 2014;Alhazaymeh et al, 2012) and further developed in decision-making processes (Tripathy and Arun, 2015;Tripathy et al, 2016;Sooraj et al, 2016Sooraj et al, , 2017, and neuro-fuzzy genetics Hassan, 2012, 2013). In view of these developments, we will introduce the notion of inverse fuzzy soft set and study its properties, structural characteristics, and operations.…”

Section: Introductionmentioning

confidence: 99%

Inverse fuzzy soft set and its application in decision making

Khalil

Hassan

2019

IJIDS

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Molodtsov introduced the theory of soft sets, which can be seen as a new mathematical approach to vagueness. In this paper, we introduce a new soft set called an inverse fuzzy soft set, along with its properties, characteristics, and operations. Then we construct an algorithm using max-min and min-max decision of inverse fuzzy soft set for a fuzzy decision-making problem. Finally, we apply the algorithm to two decision-making problems to illustrate its applicability. It is shown that our proposed approach is viable and provides decision makers a more mathematical insight before making decisions on their options.

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Fuzzy Soft Set Theory and Its Application in Group Decision Making

Cited by 20 publications

References 12 publications

Dam Safety Evaluation Based on Interval-Valued Intuitionistic Fuzzy Sets and Evidence Theory

Dam Safety Evaluation Based on Interval-Valued Intuitionistic Fuzzy Sets and Evidence Theory

A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model

Inverse fuzzy soft set and its application in decision making

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