A Hybrid Parallel Processing Strategy for Large-Scale DEA Computation

Using data envelopment analysis (DEA) with large-scale data poses a big challenge to applications due to its computing-intensive nature. So far, various strategies have been proposed in academia to accelerate the DEA computation, including DEA algorithms such as hierarchical decomposition (HD), DEA...

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Vydáno v:	Computational economics Ročník 63; číslo 6; s. 2325 - 2349
Hlavní autoři:	Chang, Shengqing, Ding, Jingjing, Feng, Chenpeng, Wang, Ruifeng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.06.2024 Springer Springer Nature B.V
Témata:	Algorithms Behavioral/Experimental Economics Computation Computer Appl. in Social and Behavioral Sciences Computing time Data analysis Data envelopment analysis Data processing Density Economic Theory/Quantitative Economics/Mathematical Methods Economics Economics and Finance Math Applications in Computer Science Message passing Multiprocessing Operations Research/Decision Theory Parallel processing Simulation Time functions Data envelopment analysis (DEA) Parallel processing Performance analysis Hierarchical decomposition (HD) Large-scale Message passing interface (MPI)
ISSN:	0927-7099, 1572-9974
On-line přístup:	Získat plný text
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