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A distributionally robust optimization for blood supply network considering disasters

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  • Wang, Changjun
  • Chen, Shutong

Abstract

We study blood supply network optimization considering disasters where only a small number of historical observations exist. A two-stage distributionally robust optimization (DRO) model is proposed, in which uncertain distributions of blood demand are described by a moment-based ambiguous set, to optimize blood inventory prepositioning and relief activities together. To solve this intractable DRO with integer recourse, an approximate way is developed to transform it into a semidefinite program. A case study, based on the Longmenshan Fault in China, validates that our approach outperforms typical benchmarks, including deterministic, stochastic and robust programming. Sensitivity analysis provides helpful managerial insights.

Suggested Citation

  • Wang, Changjun & Chen, Shutong, 2020. "A distributionally robust optimization for blood supply network considering disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    • Handle: RePEc:eee:transe:v:134:y:2020:i:c:s1366554519303886
    DOI: 10.1016/j.tre.2020.101840
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