New Model for an Open Vehicle Routing Problem to Optimize the Blood Sample Collection Process within a Network of Clinical Laboratories

Abstract

Clinical laboratories play a key role in delivering health care services, as the results of clinical tests affect 70% of medical decisions. Therefore, to provide high-quality services, smaller laboratories often send some of their samples to a well-equipped central laboratory. This study aims to minimize total transportation costs in collecting blood samples from geographically dispersed locations. Given the perishable nature of blood samples, the collection process must be completed within 2 h. Since these laboratories do not own a vehicle fleet, a third-party logistics (TPL) service provider is used in the collection process. We define this problem as a heterogenous fleet open vehicle routing problem with dynamic hub location (HFOVRP-HL). The main contribution of our work is developing a novel open vehicle routing problem (OVRP) model in which sequences of open routes and their intersections, creating dynamic and virtual hub nodes, are allowed. A mixed-integer programming (MIP) formulation is presented and solved using the CPLEX solver in GAMS, and the optimal solution is obtained. Computational results demonstrate that HFOVRP-HL outperforms classical HFOVRP, generalized HFOVRP with decoupling points (HFOVRP-DP), and HFOVRP with fixed hubs. Sensitivity analysis on key parameters confirms the model’s validity and superiority, offering substantial reductions in transportation costs. This research provides valuable insights for optimizing blood sample logistics in clinical laboratory networks.