Optimization methods in healthcare supply chains: A systematic review of methods, formulations and validation approaches (2015–2025)

This systematic review investigates optimization models applied to healthcare and pharmaceutical supply chains between 2015 and 2025, emphasizing mathematical formulations, computational methods, and validation practices. Following PRISMA-based procedures, 118 records were identified, resulting in a final sample of 37 studies. Results reveal the predominance of mixed-integer linear programming, especially in network design, facility location, inventory control, and integrated production-distribution planning. The literature also shows increasing adoption of multi-objective optimization, stochastic programming, robust optimization, heuristics, metaheuristics, and hybrid simulation-optimization approaches. Although methodological sophistication has advanced, validation practices remain concentrated in synthetic experiments, with limited real-world application. Relevant gaps include low reproducibility, scarcity of benchmark instances, and insufficient reporting of computational metrics. The review proposes a structured taxonomy of methods and a future research agenda involving scalable exact methods and integration with artificial intelligence.