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

Bayan Hamdan, Ali Diabat

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Article number101764
JournalTransportation Research Part E: Logistics and Transportation Review
StatePublished - Feb 2020


  • Blood supply chains
  • Disaster mitigation
  • Lagrangian relaxation
  • Robust optimization
  • Stochastic programming
  • Supply chain network design

ASJC Scopus subject areas

  • Business and International Management
  • Civil and Structural Engineering
  • Transportation


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