An ideal-seeking fuzzy data envelopment analysis framework

Hatami-Marbini, Adel; Saati, Saber; Tavana, Madjid

doi:10.1016/j.asoc.2009.12.031

Cited by 84 publications

(37 citation statements)

References 38 publications

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“…There are many researches that utilize that theorem such as fuzzy theorem. Fuzzy is one of the famous methods that has been applied with DEA to deal with uncertain data in decision-making process to be more adaptive to the real world [48]- [51]. Moreover, there are some researches that make use of fuzzy logic.…”

Section: B Focus and Content Of The Publicationsmentioning

confidence: 99%

A review of Data Development Analysis (DEA) applications in supply chain management research

Chaowarat

Piboonrugnroj

Shi

2013

2013 IEEE International Conference on Industrial Engineering and Engineering Management

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The objective of this paper is to review the application of Data Envelopment Analysis (DEA) in Supply Chain Management (SCM) research including different perspectives and research topics. In this review, academic databases used were ScienceDirect, Scopus and Google Scholar. The latter database was included to identify unpublished studies, conference proceedings and other types of unpublished studies. Practical review criteria are used for the inclusion or exclusion of the pertinent literature. In total 55 publications were found and analyzed in this paper. We found that even though both DEA and SCM were established as a field of study for a long time but there are only a few that applied the DEA to SCM. Most of studies applying DEA in SCM did not consider the whole supply chain, only some parts of the chain were analyzed. Based on the findings of the review, potential research agendas were developed.

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Section: B Focus and Content Of The Publicationsmentioning

confidence: 99%

A review of Data Development Analysis (DEA) applications in supply chain management research

Chaowarat

Piboonrugnroj

Shi

2013

2013 IEEE International Conference on Industrial Engineering and Engineering Management

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“…Various DEA models have been proposed to rank the DMUs during the past three decades. The concept of ''ideal DMU'' has been used to rank the DMUs in several DEA methods [22,24,30,48,[52][53][54]. Yousefi et al [61] developed an ideal DMU using the virtual network DEA approach for ranking both inefficient and efficient DMUs.…”

Section: Introductionmentioning

confidence: 99%

A hybrid goal programming and dynamic data envelopment analysis framework for sustainable supplier evaluation

Tavana

Shabanpour

Yousefi

et al. 2016

Neural Comput & Applic

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The evaluation of sustainable suppliers is one of the most complex tasks in sustainable supply chain management (SSCM). Classical data envelopment analysis (DEA) and dynamic DEA (DDEA) models are heavily dependent on historical data and do not forecast future efficiencies of decision-making units (DMUs). The primary objective of this paper is to present a new predictive paradigm for ranking sustainable suppliers in SSCM. The proposed model combines goal programming and DDEA in an integrated and seamless paradigm to determine the future efficiencies of DMUs (suppliers). It also shifts the decision maker's role from monitoring the past to planning the future. A case study is presented to demonstrate the applicability of the proposed model and exhibit the efficacy of the procedures and algorithms.

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“…Low (L) (10,20,20,30) Medium low (ML) (20,30,40,50) Medium (M) (40,50,50,60) Medium high (MH) (50,60,70,80) High (H) (70, 80, 80, 90)…”

Section: Linguistic Variable Trapezoidal Fuzzy Numbermentioning

confidence: 99%

“…Numerous fuzzy methods have been proposed to deal with this impreciseness and ambiguity in DEA since the original study by Sengupta. 19 In general, fuzzy DEA methods can be classified into four primary categories, namely, the tolerance approach (Sengupta 19 ), the α-level based approach (Kao and Liu, 28 Saati et al, 29 Hatami-Marbini et al 30 ), the fuzzy ranking approach (Guo and Tanaka 31 ) and the possibility approach (Lertworasirikul et al 32 ). An exhaustive review and taxonomy of various fuzzy DEA models can be found in HatamiMarbini et al 33 Clustering is the process of organizing a set of objects (operating units) into a useful set of mutually exclusive clusters such that the similarity of the objects within a cluster is maximized while the similarity of the objects between different clusters is minimized (e.g., Jain et al, 34 Okazaki, 35 Rai et al, 36 Samoilenko and Osei-Bryson, 37 Wallace et al 38 ).…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Data Envelopment Analysis for Clustering Operating Units With Imprecise Data

Saati

Hatami-Marbini

Tavana

et al. 2013

Int. J. Unc. Fuzz. Knowl. Based Syst.

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Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiency of peer operating units that employ multiple inputs to produce multiple outputs. Several DEA methods have been proposed for clustering operating units. However, to the best of our knowledge, the existing methods in the literature do not simultaneously consider the priority between the clusters (classes) and the priority between the operating units in each cluster. Moreover, while crisp input and output data are indispensable in traditional DEA, real-world production processes may involve imprecise or ambiguous input and output data. Fuzzy set theory has been widely used to formalize and represent the impreciseness and ambiguity inherent in human decision-making. In this paper, we propose a new fuzzy DEA method for clustering operating units in a fuzzy environment by considering the priority between the clusters and the priority between the operating units in each cluster simultaneously. A numerical example and a case study for the Jet Ski purchasing decision by the Florida Border Patrol are presented to illustrate the efficacy and the applicability of the proposed method.

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An ideal-seeking fuzzy data envelopment analysis framework

Cited by 84 publications

References 38 publications

A review of Data Development Analysis (DEA) applications in supply chain management research

A review of Data Development Analysis (DEA) applications in supply chain management research

A hybrid goal programming and dynamic data envelopment analysis framework for sustainable supplier evaluation

A Fuzzy Data Envelopment Analysis for Clustering Operating Units With Imprecise Data

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