A hierarchical model for strategic and operational planning in blood transportation with drones

Abstract

Blood transportation is a critical aspect of the healthcare systems, ensuring whole blood and blood products are delivered to patients in a timely and efficient manner. However, transportation of blood and other medical supplies can be challenging, especially in urban areas with limited infrastructure and heavy traffic. Drones have become increasingly important in recent years as a means of delivering medical supplies, including blood, due to their ability to provide fast, reliable, and cost-effective transportation. This study proposes two mathematical programming models in the hierarchical structure to improve decision-making for strategic and operational planning in the blood supply chain network. The limited information available in strategic planning presents risks to the blood supply chain, making it imperative to address uncertainties. To tackle this challenge, a novel approach called Scenario-based Robust Bi-objective Optimization has been proposed. The first model employs this approach to efficiently handle demand uncertainty by simultaneously maximizing the covered demand and minimizing costs. The model is subsequently solved using the augmented ε-constraint method. The second model is a routing-scheduling operational model that aims to minimize the sum of operations time, taking into account time windows for blood collection centers and hospitals. The developed hierarchical model is implemented in a three-level supply chain of Tehran province under three crisis scenarios in different parts. The findings and analysis of this implementation suggest that it is beneficial to set up drone stations in cost-effective and central locations to avoid costly network design. Furthermore, utilizing the minimum number of feasible drones enhances operational time and results in cost savings and increased efficiency. Overall, this study highlights the potential of using drones for blood transportation in urban settings, which can have significant implications for improving the quality of healthcare delivery.

Risk assessment of organ transplant operation: A fuzzy hybrid MCDM approach based on fuzzy FMEA

“…The inherent characteristics of the world give rise to numerous uncertainties, each exerting diverse impacts on different issues [ 66 , 67 ]. Fuzzy logic is an approach used to evaluate systems that have elements of uncertainty [ 68 ].…”

Emerging Research Topics in Drone Healthcare Delivery

“…Although both themes investigated the efficiency and cost-effectiveness of UAV delivery, the way these aspects were discussed in the literature differed. The distinction may stem from studies on UAVs in healthcare supply chains being grounded in real-world scenarios [16,27,80], whilst research on UAVs for time-critical medical deliveries has largely relied upon simulated data [80][81][82][83].…”