A taxonomy for data envelopment analysis

Gattoufi, Said; Oral, Muhittin; Reisman, Arnold

doi:10.1016/s0038-0121(03)00022-3

Cited by 84 publications

(35 citation statements)

References 32 publications

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“…For a complete introduction into DEA we refer to (Cooper, Seiford, & Tone, 2000) or (Thanassoulis, 2001). A taxonomy of DEA approaches is ready available (Gattoufi, Oral, & Reisman, 2004), and also an update on how DEA developed in the last three decades (Cook & Seiford, 2009). …”

Section: Data Envelopment Analysismentioning

confidence: 99%

Contrasting ERP Absorption Between Transition and Developed Economies From Central and Eastern Europe (CEE)

Bernroider

Sudzina

Pucihar

2011

Information Systems Management

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Section: Data Envelopment Analysismentioning

confidence: 99%

Contrasting ERP Absorption Between Transition and Developed Economies From Central and Eastern Europe (CEE)

Bernroider

Sudzina

Pucihar

2011

Information Systems Management

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“…The attribute vector description-based taxonomy method developed by Reisman [74] is used. It has been used for the classification of vehicle routing problem [75] and data envelopment analysis [76]. The attribute vector description-based taxonomy method proceeds in an arborescent way, as shown in Fig.…”

Section: Fjsp Taxonomymentioning

confidence: 99%

A Taxonomy for the Flexible Job Shop Scheduling Problem

Çınar

Topçu

Oliveira

2015

Springer Proceedings in Mathematics &Amp; Statistics

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This chapter aims at developing a taxonomic framework to classify the studies on the flexible job shop scheduling problem (FJSP). The FJSP is a generalization of the classical job shop scheduling problem (JSP), which is one of the oldest NP-hard problems. Although various solution methodologies have been developed to obtain good solutions in reasonable time for FSJPs with different objective functions and constraints, no study which systematically reviews the FJSP literature has been encountered. In the proposed taxonomy, the type of study, type of problem, objective, methodology, data characteristics, and benchmarking are the main categories. In order to verify the proposed taxonomy, a variety of papers from the literature are classified. Using this classification, several inferences are drawn and gaps in the FJSP literature are specified. With the proposed taxonomy, the aim is to develop a framework for a broad view of the FJSP literature and construct a basis for future studies.

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“…DEA applications involve a wide range of context such as education, health care, banking, market research, transportation, courts, public housing, airports, manufacturing and etc,. For taxonomy of DEA applications interested readers should look at the paper by Gattoufi, et al [11].…”

Section: Deamentioning

confidence: 99%