Green and cold-chain pharmaceutical supply chain planning under budget constraints and inflation effects in an international context

This study develops a bi-objective linear programming (BOLP) model for pharmaceutical supply chain (PSC) planning. The model integrates cold-chain temperature-control requirements, budget constraints, and inflation effects within a green supply chain (GSC) framework. The model simultaneously minimizes total operational costs and environmental impacts while ensuring the quality and safety of temperature-sensitive pharmaceutical products. The PSC is modeled as a three-echelon network comprising manufacturers and importers, distribution centers, and end-user points, such as healthcare facilities. The formulation captures key operational decisions related to production, importation, inventory management, transportation, and storage over a multi-period planning horizon. To reflect real-world economic conditions, operational cost parameters are adjusted over time using an inflation factor, as detailed in the model formulation. Environmental performance is evaluated based on carbon dioxide (CO₂) emissions from transportation activities and hydrofluorocarbon (HFC) emissions from refrigerated storage and transportation systems. The proposed BOLP model is implemented in Python and solved using IBM ILOG CPLEX to evaluate system performance under different operational conditions. The results show that production, importation, transportation, and inventory decisions significantly affect both economic and environmental objectives. In addition, there exists a clear trade-off between minimizing total cost and reducing environmental impacts. Overall, the proposed model provides a decision-support framework for improving the economic and environmental performance of green and cold-chain PSCs under inflationary conditions in an international context.