Optimizing Healthcare Logistics with Hybridngs for Blood Bag Delivery Using Drones: Hybridngs Algorithm [Hybrid Nearest Neighbour, Genetic Algorithm, Simulated Annealing] for Drone Routing”

Abstract

Blood product transportation within hospital networks necessitates timely and secure handling, which requires effective management of blood supply logistics. This becomes particularly accurate when facing challenges such as unpredictable terrain and congestion.  Drone technology is being explored as a disruptive force in supply chain management due to the limitations faced by traditional land-based transportation methods. Introducing drones into the blood supply chain brings about complexities that require new approaches to route planning, resource allocation, and scheduling. The HybridNGS algorithm, which leverages the strengths of three  algorithms, addresses the following challenges: Nearest Neighbor (NN), Genetic Algorithms (GA), and Simulated Annealing (SA). The effectiveness of blood supply chain logistics is aimed to be enhanced by this hybrid model through careful integration. Through the effective exploration of limited areas by NN, the generation of diverse solutions by GA, and the solution enhancement capabilities of SA, nearly optimal solutions are found in complex solution spaces within the hospitals network. The process of optimization takes into account actual constraints, such as the maximum capacity of the drone, the minimum safe distance from the ground, valid routes, and the restricted distance the drone can fly. This article discusses the HybridNGS Algorithm, which is used to optimize drone routing for blood supply logistics. The algorithm has been carefully customized to specifically handle the important and delicate matter of managing the supply of blood bags in hospital networks. The algorithm has been shown effective via thorough study and assessment of its effectiveness in enhancing logistics. Thus, it has improved healthcare accessibility, particularly in distant places and areas with heavy traffic congestion.

Keywords: Healthcare logistics, Emerging transport modes, Experiment, Drone routing problem