For the past few years, pharmaceutical logistics has undergone significant changes, especially in the period referred to as the post-pandemic era, which brought major transformations to healthcare systems around the world. This research provides a novel model to enhance pharmaceutical supply chain services by routing, locating, and allocating urgent and non-urgent patients to home delivery services or automated medicine lockers. Two scenarios are proposed, with one scenario considering two types of vehicles and creating different routes to deliver medicine to automated medicine lockers or patients, and the other not distinguishing between them. The proposed mixed integer linear programming model uses a three-objective for the green open vehicle routing problem to identify the routing total costs, greenhouse gas emissions under varying speed levels due to risk of traffic congestion, and patient satisfaction. The concept of triage is also embedded into the model to prevent assigning the urgent patients to automated medicine lockers as much as possible. The problem is solved using an improved non-dominated sorting genetic algorithm-II and the LP-metric method, verified through real-world applications. Although experimental studies justify applying automated medicine lockers to cut costs significantly, 14.74% for the first scenario and 13.511% for the second, the resulted model also highlights its application to optimizing home healthcare performance. It is achieved by including greenhouse gas emissions and patient satisfaction within the framework and utilizing automated medicine lockers for pharmacy supply chain services improvement.
Bahrami et al. (Fri,) studied this question.