A Robust Contract-Based Hybrid Procurement Model with Supplier Incentives for Humanitarian Supply Chains under Uncertainty

Author

Assistant Professor, School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.

Abstract

Typically, humanitarian agencies (HAs) tend to preposition relief supplies before potential disasters to increase resource availability in the post-disaster phase. However, prepositioning imposes high costs on relief chains. On the other hand, although postponing relief supply procurement to the post-disaster phase may avoid prepositioning costs, it comes with significant supply risks. This study utilizes buyback, option, and quantity discount contracts which enables HAs to adopt a hybrid strategy for providing relief supplies, ensuring maximum post-disaster supply availability. In this paper, a robust bi-objective two-stage stochastic programming model is proposed for supplier selection and the procurement of critical and non-critical relief supplies. The model also emphasizes suppliers' profits to incentivize their participation in the relief chain. In this study, a combination of robust stochastic programming and robust convex programming is employed to manage uncertainty. The model is applied to a case study, and multiple sensitivity analyses are performed. The results demonstrate that, compared with the situation in which hybrid contracts are not utilized, the proposed model reduces the HA’s cost by 38.4% and expected shortages by 22.6%, while increasing suppliers’ profits by 41.8%.

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References

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Advances in Industrial Engineering
Volume 60, Issue 1
June 2026
Pages 71-92

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