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A Mathematical Model Under Uncertainty for Optimizing Medicine Logistics in Hospitals
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Autores
Franco Franco, Carlos Alberto
López-Santana E.R.
Figueroa-García J.C.
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Fecha
2018
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Springer Verlag
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Abstract
Managing resources in hospitals is one of the most challenging duties in healthcare. The complexity of supply chain management in hospitals is high due to different factors such as life cycle of medicines, demand uncertainty, variation of prices, monetary resources, space constraints, among others. The main important factor of the supply chain in hospitals is the welfare of patients which depends of the correct management and administration of medicines, in this way backorders or stockouts are not allowed. In this paper we propose a mathematical model to make real planning over a health care supply chain considering real factors face by decision makers. For testing results we have used real data considering different sources of uncertainty. We have choose 5 different types of medicines and run the optimization model to determine the optimal solution over a set of scenarios generated for modeling uncertainty. For testing the results, we have compare over a year planning the results obtained by our policy and the results obtained by the hospital, improving the results in terms of costs. © 2018, Springer Nature Switzerland AG.
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Keywords
Decision making , Health care , Hospitals , Life cycle , Optimization , Uncertainty analysis , Demand uncertainty , Managing resources , Model uncertainties , Monetary resources , Optimal solutions , Optimization modeling , Robust optimization , Sources of uncertainty , Supply chain management , Hospital planning , Optimization , Optimization under scenarios , Pharmaceutical logistics , Robust optimization
