A Parametric Method for Ranking Intuitionistic Fuzzy Numbers and Its Application to Solve Intuitionistic Fuzzy Network Data Envelopment Analysis Models

Shakouri, B.; Shureshjani, Roohollah Abbasi; Daneshian, Behrouz; Lotfı, Farhad Hosseinzadeh

doi:10.1155/2020/6408613

Cited by 16 publications

(8 citation statements)

References 46 publications

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“…is paper is a special type of the two-stage DEA model in variable returns to scale case in which all variables are expressed by TIFNs. Comparing the proposed model of the present study with the proposed model of Shakouri et al [52], it can be stated that the proposed model of Shakouri et al has not been used for all intuitionistic fuzzy data. e proposed two-stage model compared to Shakouri et al has more power and application in the real world due to all intuitionistic fuzzy data and due to the intuitionistic fuzzy environment and two stages of the model, and the overall structure and each of the stages are separable and rankable which has made the model a unique advantage over other models.…”

Section: Discussionmentioning

confidence: 73%

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Designing an Intuitionistic Fuzzy Network Data Envelopment Analysis Model for Efficiency Evaluation of Decision-Making Units with Two-Stage Structures

Javaherian

Hamzehee

Tooranloo

2021

Advances in Fuzzy Systems

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Data envelopment analysis (DEA) is a powerful tool for evaluating the efficiency of decision-making units for ranking and comparison purposes and to differentiate efficient and inefficient units. Classic DEA models are ill-suited for the problems where decision-making units consist of multiple stages with intermediate products and those where inputs and outputs are imprecise or nondeterministic, which is not uncommon in the real world. This paper presents a new DEA model for evaluating the efficiency of decision-making units with two-stage structures and triangular intuitionistic fuzzy data. The paper first introduces two-stage DEA models, then explains how these models can be modified with intuitionistic fuzzy coefficients, and finally describes how arithmetic operators for intuitionistic fuzzy numbers can be used for a conversion into crisp two-stage structures. In the end, the proposed method is used to solve an illustrative numerical example.

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Section: Discussionmentioning

confidence: 73%

“…Most studies in the field of DEA in IF environment are about a single-stage models. Among studies in network models, we can mention the study of Shakouri et al [52]. ey used the NDEA model in series and parallel structures.…”

Section: Discussionmentioning

confidence: 99%

Designing an Intuitionistic Fuzzy Network Data Envelopment Analysis Model for Efficiency Evaluation of Decision-Making Units with Two-Stage Structures

Javaherian

Hamzehee

Tooranloo

2021

Advances in Fuzzy Systems

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“…Edalatpanah (2019) proposed a ranking approach for solving the intuitionistic fuzzy DEA model. Shakouri et al (2020) proposed the intuitionistic fuzzy network DEA model based on a parametric approach. Arya and Yadav (2020a) developed the intuitionistic fuzzy BCC model and intuitionistic fuzzy super efficiency BCC model with TIFNs input/output data and studied the infeasibility of IFDEA models.…”

Section: Introductionmentioning

confidence: 99%

A Novel Technique for Solving Intuitionistic Fuzzy DEA Model: An Application in Indian Agriculture Sector

Mohanta

Sharanappa

2023

Preprint

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Fuzzy DEA is a performance measurement tool that is used to assess the performance of DMUs in highly uncertain environment. In this article, the Intuitionistic fuzzy DEA (IFDEA) model is proposed based on the triangular intuitionistic fuzzy numbers (TIFNs). The weighted Possibility mean for TIFNs are used to compare and rank the TIFN. The weighted possibility mean approach is proposed to solve IFDEA model that the IFDEA model is converted into its equivalent crisp DEA model to assess the relative efficiencies of the DMUs. One advantage of the proposed approach is that the attitude of the decision maker is considered while measuring the efficiency of the DMUs. The weight or risk factor δ ∈ [0, 1] indicates whether the decision maker is a risk taker, neutral, or adverse. The crisp DEA model is a LP problem that is solved by using an existing LP method with different risk factors to determine the efficiency score of the DMUs. The DMUs are ranked based on the overall efficiency score of the DMUs that is arithmetic mean of the efficiency scores of the DMUs with different risk factors. Two numerical example is given here to demonstrate the validity and applicability of the proposed technique and to compare the performance of the DMUs in the proposed approach with exciting ranking approach and expected value approach. A case study on the agriculture sector has been conducted in order to evaluate the agricultural performance of Indian states using the IFDEA model. According to the results of the IFDEA model, 15 (53.57%) out of the 28 Indian states were found to be efficient.

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Section: Introductionmentioning

confidence: 99%

A Novel Technique for Solving Intuitionistic Fuzzy DEA Model: An Application in Indian Agriculture Sector

Mohanta

Sharanappa

Edalatpanah

2023

Preprint

View full text Add to dashboard Cite

Fuzzy DEA is a performance measurement tool that is used to assess the performance of DMUs in highly uncertain environment. In this article, the Intuitionistic fuzzy DEA (IFDEA) model is proposed based on the triangular intuitionistic fuzzy numbers (TIFNs). The weighted Possibility mean for TIFNs are used to compare and rank the TIFN. The weighted possibility mean approach is proposed to solve IFDEA model that the IFDEA model is converted into its equivalent crisp DEA model to assess the relative efficiencies of the DMUs. One advantage of the proposed approach is that the attitude of the decision maker is considered while measuring the efficiency of the DMUs. The weight or risk factor δ є [0,1] indicates whether the decision maker is a risk taker, neutral, or adverse. The crisp DEA model is a LP problem that is solved by using an existing LP method with different risk factors to determine the efficiency score of the DMUs. The DMUs are ranked based on the overall efficiency score of the DMUs that is arithmetic mean of the efficiency scores of the DMUs with different risk factors. Two numerical example is given here to demonstrate the validity and applicability of the proposed technique and to compare the performance of the DMUs in the proposed approach with exciting ranking approach and expected value approach. A case study on the agriculture sector has been conducted in order to evaluate the agricultural performance of Indian states using the IFDEA model. According to the results of the IFDEA model, 15 (53.57%) out of the 28 Indian states were found to be efficient.

show abstract

A Parametric Method for Ranking Intuitionistic Fuzzy Numbers and Its Application to Solve Intuitionistic Fuzzy Network Data Envelopment Analysis Models

Cited by 16 publications

References 46 publications

Designing an Intuitionistic Fuzzy Network Data Envelopment Analysis Model for Efficiency Evaluation of Decision-Making Units with Two-Stage Structures

Designing an Intuitionistic Fuzzy Network Data Envelopment Analysis Model for Efficiency Evaluation of Decision-Making Units with Two-Stage Structures

A Novel Technique for Solving Intuitionistic Fuzzy DEA Model: An Application in Indian Agriculture Sector

A Novel Technique for Solving Intuitionistic Fuzzy DEA Model: An Application in Indian Agriculture Sector

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