Journal
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
Volume 134, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tre.2019.08.005
Keywords
Blood supply chains; Disaster mitigation; Robust optimization; Supply chain network design; Stochastic programming; Lagrangian relaxation
Categories
Funding
- NYUAD Center for Interacting Urban Networks (CITIES) - Tamkeen under the NYUAD Research Institute Award [CG001]
- Swiss Re Institute under the Quantum Cities(TM) initiative
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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.
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