An SBM-DEA model with parallel computing design for environmental efficiency evaluation in the big data context: a transportation system application

DOI10.1007/s10479-016-2264-7zbMath1412.90062OpenAlexW2462592853MaRDI QIDQ1730503

Malin Song, Jie Wu, Jun-Fei Chu

Publication date: 6 March 2019

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-016-2264-7

zbMATH Keywords

data envelopment analysisparallel computingbig dataenvironmental efficiencySBM modelslacks-based measure model

Mathematics Subject Classification ID

Related Items (6)

Parallel processing of the Build Hull algorithm to address the large-scale DEA problem ⋮ Assessing sustainability of supply chains by double frontier network DEA: a big data approach ⋮ Variable selection in data envelopment analysis via Akaike's information criteria ⋮ Efficiency evaluation of very large-scale samples: data envelopment analysis with angle-index synthesis ⋮ Interval cross efficiency for fully ranking decision making units using DEA/AHP approach ⋮ Big data in humanitarian supply chain management: a review and further research directions

Uses Software

• DEA

Cites Work

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