Identifying the most influential employees in infectious disease spread using stochastic mixed integer linear programming optimization.
| Publicado en: | Health Care Management Science Vol. 29; no. 1; pp. 1 - 21 |
|---|---|
| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Mar2026
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=192061390&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 192061390 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13869620 BSE jtl: Health Care Management Science issn: 13869620 maglogo: N pubinfo: dt: Mar2026 vid: 29 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 192061390 10.1007/s10729-025-09744-4 192061390 ppf: 1 ppct: 20 formats: tig: atl: Identifying the most influential employees in infectious disease spread using stochastic mixed integer linear programming optimization. aug: au: Basirati, Mohadese Najafi-Zangeneh, Saeed Batton-Hubert, Mireille affil: https://ror.org/01a8ajp46 Industrial Engineering and Applied Mathematics Department, Mines Saint-Etienne, Univ Clermont Auvergne, INP Clermont Auvergne, CNRS, UMR 6158 LIMOS, Saint-Etienne, France sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|