A new integrated AR-IDEA model to find the best DMU in the presence of both weight restrictions and imprecise data

Ebrahimi, Bohlool; Khalili, Masoud

doi:10.1016/j.cie.2018.09.008

Cited by 14 publications

(6 citation statements)

References 40 publications

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“…They claimed that their model has more discrimination power than the existing mixed integer DEA approaches. Ebrahimi and Khalili (2018) developed the following new mixed integer DEA model (5) to identify the best efficient unit in the presence of both assurance region type 1 and different types of imprecise data.…”

Section: Literature Reviewmentioning

confidence: 99%

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Efficiency measurement to identify the best efficient unit in the presence of dual-role factors

Ebrahimi

2020

IJADS

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Efficiency measurement is crucial to management for performance evaluation of several decision-making units (DMUs) in order to find the most efficient unit. Data envelopment analysis (DEA) is a practical and popular method that has been used widely for efficiency measurement in many applications. Thus, in the literature of DEA, several mixed integer DEA models are developed to efficiency measure and find the best efficient unit. In some situations, some factors named dual-role factors may be simultaneously considered as both inputs and outputs. However, a little attention has been paid in the literature of DEA to these types of factors. The current paper develops a new mixed integer linear DEA model to identify the best efficient DMU in the presence of dual-role factors. The basic DEA models consider different roles for each dual-role factor, and also solve at least one model for each DMU to determine the best unit. However, the developed approach in this paper considers a unique role for each dual-role factor, and also determines the best unit through by solving just one mixed integer DEA model. Two numerical examples are used to illustrate the profits and applicability of the developed approach.

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Section: Literature Reviewmentioning

confidence: 99%

“…It should be here emphasised that the approach of Saen (2010) uses the weight restriction that can improve the discrimination power of DEA models (Ebrahimi and Khalili, 2018). Table 2 summarised the results of the proposed approach in this paper along with Saen (2010) and Cook et al (2006).…”

Section: Numerical Illustrationmentioning

confidence: 99%

Efficiency measurement to identify the best efficient unit in the presence of dual-role factors

Ebrahimi

2020

IJADS

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“…Moreover, Zhu (2003) developed a linear programming model handling strong ordinal inputs and outputs. Also, Ebrahimi and Khalili (2018) proposed the modelsincorporating preference information-that find the most preferred DMU and rank other efficient DMUs. The DEA models handling imprecise data have been successfully used in the telecommunication sector (Cooper et al 2001), machinery industry (Kao and Liu 2005), wheat farming (Hadi-Vencheh and Matin 2011), port efficiency assessment (Zahran et al 2020), and healthcare (see Azadi and Saen 2013;Karsak and Karadayi 2017).…”

Section: Introductionmentioning

confidence: 99%

Exact and stochastic methods for robustness analysis in the context of Imprecise Data Envelopment Analysis

Labijak-Kowalska

Kadziński

2023

Oper Res Int J

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We consider the problem of measuring the efficiency of decision-making units with a ratio-based model. In this perspective, we introduce a framework for robustness analysis that admits both interval and ordinal performances on inputs and outputs. The proposed methodology exploits the uncertainty related to the imprecise data and all feasible input/output weight vectors delimited through linear constraints. We offer methods for verifying the robustness of three types of outcomes: efficiency scores, efficiency preference relations, and efficiency ranks. On the one hand, we formulate mathematical programming models to compute the extreme, necessary, and possible results. On the other hand, we incorporate the stochastic analysis driven by the Monte Carlo simulations to derive the probability distribution of different outcomes. The framework is implemented in R and made available on open-source software. Its use is illustrated in two case studies concerning Chinese ports or industrial robots.

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“…Cone ratio approach is a more generalized version introduced by Charnes et al [9] in which the input and output weights are restricted to belong to the related polyhedral convex cones each of which spanned by a finite number of admissible non-negative direction vectors. For further information see [19], [21], [39], [10], and [35].…”

Section: Introductionmentioning

confidence: 99%

A novel ranking approach with common weights: An implementation in the presence of interval data and flexible measures

Ramezani-Tarkhorani

Eini

2022

RAIRO-Oper. Res.

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In this paper a ranking method using common weights methodology is presented. The goal of the method is enhancing the decision maker (DM)’s influence in the ranking procedure. Although DM’s preference information is an important element in our method, the approach can also be modified to be used in the absence of it. Since we aim to implement the approach on an empirical instance, the model is modified to deal with the properties of the sample, so it is developed in the presence of the interval data and flexible measures. Finally, the results are discussed.

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A new integrated AR-IDEA model to find the best DMU in the presence of both weight restrictions and imprecise data

Cited by 14 publications

References 40 publications

Efficiency measurement to identify the best efficient unit in the presence of dual-role factors

Efficiency measurement to identify the best efficient unit in the presence of dual-role factors

Exact and stochastic methods for robustness analysis in the context of Imprecise Data Envelopment Analysis

A novel ranking approach with common weights: An implementation in the presence of interval data and flexible measures

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