Robust design of blood supply chains under risk of disruptions using Lagrangian relaxation

Bayan Hamdan and Ali Diabat

Transportation Research Part E: Logistics and Transportation Review, 2020, vol. 134, issue C

Abstract: Emergency supply of blood in disasters is a crucial task for humanitarian aid. In this paper, we present a bi-objective robust optimization model for the design of blood supply chains that are resilient to disaster scenarios. The proposed two-stage stochastic optimization model aims at minimizing the time and cost of delivering blood to hospitals after the occurrence of a disaster, while considering possible disruptions in blood facilities and transportation routes. A Lagrangian relaxation-based algorithm is developed that is capable of solving large-scale instances of the model. We apply this framework to a real case study of blood banks in Jordan.

Keywords: Blood supply chains; Disaster mitigation; Robust optimization; Supply chain network design; Stochastic programming; Lagrangian relaxation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (31)

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DOI: 10.1016/j.tre.2019.08.005

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