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Mixed integer programming model for reverse logistics in the management of Covid vaccination waste in health facilities located in marginal areas: Case study of North Lima - Peru

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Date
2023
Author(s)
Taquía Gutiérrez, José Antonio
Bonilla Orrillo, Diego Alexis
Laureano Adriano, Carla
Metadata
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Abstract
The public health policies applied to mitigate the effect of the Covid 19 pandemic posed a logistical challenge due to their complexity as well as having to be implemented in the shortest possible time. In this paper we present a model applied in a low-income area in Lima, Peru. A mixed integer optimization model was designed for 32 health centers geographically distributed in areas far from the waste disposal centers and the sequence and route of waste collection was determined to minimize the cost of travel and meet the largest possible amount of vaccine waste.
URI
https://hdl.handle.net/20.500.12724/18514
DOI
https://doi.org/10.1145/3587889.3587963
How to cite
Bonilla Orrillo, D. A., Laureano Adriano, C., & Taquía Gutiérrez, J. A. (2023, January). Mixed integer programming model for reverse logistics in the management of Covid vaccination waste in health facilities located in marginal areas: Case study of North Lima-Peru. In Proceedings of the 2023 10th International Conference on Industrial Engineering and Applications (pp. 35-40). https://doi.org/10.1145/3587889.3587963
Publisher
Association for Computing Machinery
Subject
Vacunación
Gestión de residuos
Residuos sanitarios
Logística
Vaccination
Refuse and refuse disposal
Medical wastes
Logistics
COVID-19
Lima (Perú)
Event
ACM International Conference Proceeding Series
Collections
  • Ingeniería Industrial [182]


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