How to improve the future efficiency of Covid-19 treatment centers? A hybrid framework combining artificial neural network and congestion approach of data envelopment analysis

Saeed Yousefi, Hadi Shabanpour, Kian Ghods et Reza Farzipoor Saen

Article de revue (2023)

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Département:	Département de mathématiques et de génie industriel
URL de PolyPublie:	https://publications.polymtl.ca/53306/
Titre de la revue:	Computers & Industrial Engineering (vol. 176)
Maison d'édition:	Elsevier
DOI:	10.1016/j.cie.2022.108933
URL officielle:	https://doi.org/10.1016/j.cie.2022.108933
Date du dépôt:	18 avr. 2023 14:58
Dernière modification:	25 sept. 2024 16:44

Citer en APA 7:	Yousefi, S., Shabanpour, H., Ghods, K., & Saen, R. F. (2023). How to improve the future efficiency of Covid-19 treatment centers? A hybrid framework combining artificial neural network and congestion approach of data envelopment analysis. Computers & Industrial Engineering, 176, 108933 (11 pages). https://doi.org/10.1016/j.cie.2022.108933
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