Please use this identifier to cite or link to this item:
https://repository.iimb.ac.in/handle/2074/17776
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Krishnamurthy, Ananth | |
dc.contributor.author | Limon, Yasemin | |
dc.date.accessioned | 2021-03-26T15:16:30Z | - |
dc.date.available | 2021-03-26T15:16:30Z | - |
dc.date.issued | 2020 | |
dc.identifier.issn | 2472-5854 | |
dc.identifier.issn | 2472-5862 | |
dc.identifier.uri | https://repository.iimb.ac.in/handle/2074/17776 | - |
dc.description.abstract | We analyze resource allocation challenges in protein purification operations where differences in scientist capabilities can lead to significantly different outcomes. We use queuing models to capture the underlying dynamics and quantify the performance of different strategies based on solutions obtained using the matrix-geometric approach. We show that certain partial flexibility structures coupled with appropriate priority rules can yield very efficient system performance. We also define a new server utilization metric that can be very effective in rank ordering strategies. Through numerical studies, we provide useful rules for the biomanufacturers to achieve higher profits and shorter lead times. | |
dc.publisher | Taylor and Francis | |
dc.subject | Resource allocation | |
dc.subject | Biomanufacturing | |
dc.subject | Protein purification | |
dc.subject | Matrix-geometric approach | |
dc.title | Resource allocation strategies for protein purification operations | |
dc.type | Journal Article | |
dc.identifier.doi | 10.1080/24725854.2019.1680908 | |
dc.pages | 945-960p. | |
dc.vol.no | Vol.52 | |
dc.issue.no | Iss.9 | |
dc.journal.name | IISE Transactions | |
Appears in Collections: | 2020-2029 C |
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