Name
Abstract | ||
|---|---|---|
•A new framework is proposed to deal with large-scale data envelopment analysis.•Decreases the computational time to measure the performance scores of big data sets.•The fastest available data envelopment analysis technique for big data.•A framework of choice to evaluate large-scale data envelopment analysis.•Our method is easy to implement. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.ejor.2018.10.044 | European Journal of Operational Research |
Keywords | Field | DocType |
Data envelopment analysis (DEA),Big data,Performance evaluation,Simulation | Electric power,Mathematical optimization,Cardinality,Data envelopment analysis,Hull,Big data,Mathematics,Returns to scale,Computation | Journal |
Volume | Issue | ISSN |
274 | 3 | 0377-2217 |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dariush Khezrimotlagh | 1 | 35 | 3.00 |
| Joe Zhu | 2 | 1762 | 167.31 |
| Wade D. Cook | 3 | 1215 | 84.70 |
| Mehdi Toloo | 4 | 118 | 17.92 |