Metaheuristic Tabu Search for Vehicle Scheduling: A Case Study of Healthcare Logistics

Healthcare logistics is one of the most complex networks affecting the delivery of health and well-being of individuals. Efficient management of last-mile delivery, i.e., the final stage of the logistics chain, is paramount to fulfilling customer promises. Despite extensive research efforts dedicated to tackling these issues through the lens of vehicle routing problem (VRP) and its variants, it remains unclear whether the challenges addressed in the research domains hold practical significance in real-world scenarios, which are often more complex, uncertain, and highly constrained. Therefore, this article presents a proof-of-concept pertaining to the implementation of the Tabu Search (TS) algorithm as a software solution for optimizing delivery routes in the real-world healthcare logistics sector. The software is developed following a stringent systems development life cycle (SDLC). The effectiveness of the developed system is validated through three distinct daily logistics scenarios.