Sustainability and Algorithmic Comparison of Segmented PVRP for Healthcare Waste Collection: A Brazilian Case Study

The safe and sustainable management of healthcare waste (HCW) is essential for minimizing environmental impacts and protecting public health, particularly in developing countries with limited logistical infrastructure. Despite the growing adoption of routing optimization in HCW logistics, few studies integrate waste generator segmentation with algorithmic planning. This study proposes an optimization approach based on the Periodic Vehicle Routing Problem (PVRP), incorporating a segmentation of waste generators by volume. Two solution methods, the Clarke and Wright (CW) heuristic and Particle Swarm Optimization (PSO), are applied and compared through a real-world case study in Paraná, Brazil. Results show that PSO significantly outperforms CW in reducing travel distance and CO2 emissions. For small generators, PSO achieves reductions of up to 41% in distance and 41.37% in emissions, compared to CW’s 35.42%. For large generators, PSO was reduced by 22% and 21.81%, respectively. The proposed method demonstrates the potential for scalable, data-efficient waste management strategies. This research contributes to sustainable urban logistics by bridging segmentation and routing optimization in resource-constrained settings, offering actionable insights for policymakers and planners.