The healthcare supply location-inventory-routing problem: A robust approach

Motivated by a real-world healthcare supply case of a medical implant company, this paperstudies a supply network configuration problem that integrates warehouse selections forvendor managed inventory (VMI), inventory policy, and delivery routing optimization together.The problem is a variant of the classic location-inventory-routing problem (LIRP) with bothdeterministic demand and uncertain demand, where multi-product, multi-period, multi-typedelivery, delivery time limit and VMI are considered. Two types of delivery are used: one is thescheduled bulk delivery to the VMI warehouses and the other is direct shipping for hospitals.To address the problem, first, a deterministic MILP model is presented for the integrated LIRP.Then, to deal with the uncertainty in demand, we propose a robust optimization model andtransform it into a tractable linear equivalent formulation. Further, considering the effect ofCOVID-19 pandemic on the demand and delivery time, a new robust model is proposed toaccount for this special situation. Numerical experiments are conducted to verify the advantageof the proposed robust optimization models. The sensitivity analysis provides some interestingmanagerial insights, and a real-world case of medical implant supply configuration with 78hospitals is solved.

Automated summary

Motivated by a real-world healthcare supply case, this paper examines a supply network configuration problem that integrates warehouse selections, inventory policy, and delivery routing optimization. It proposes deterministic and robust optimization models to address uncertain demand and considers the impact of COVID-19 pandemic. Numerical experiments and a real-world case study provide insights into the proposed models.