TY - GEN
T1 - A Mathematical Model Under Uncertainty for Optimizing Medicine Logistics in Hospitals
AU - Franco, Carlos
AU - López-Santana, Eduyn Ramiro
AU - Figueroa-García, Juan Carlos
N1 - Publisher Copyright:
© 2018, Springer Nature Switzerland AG.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-030-00353-1_5
DO - 10.1007/978-3-030-00353-1_5
M3 - Conference contribution
AN - SCOPUS:85053994555
SN - 9783030003524
T3 - Communications in Computer and Information Science
SP - 53
EP - 60
BT - Applied Computer Sciences in Engineering - 5th Workshop on Engineering Applications, WEA 2018, Proceedings
A2 - Maya Duque, Pablo Andres
A2 - Villegas, Juan G.
A2 - Figueroa-García, Juan Carlos
A2 - Orozco-Arroyave, Juan Rafael
PB - Springer
T2 - 5th Workshop on Engineering Applications, WEA 2018
Y2 - 17 October 2018 through 19 October 2018
ER -