A fuzzy robust stochastic model for designing a pharmaceutical supply chain with sustainability and resiliency dimensions

The importance of pharmaceutical supply chains in ensuring the health of communities is obvious to everyone. In the event of a crisis, the importance of pharmaceutical supply chains becomes more visible, and paying attention to the dimensions of sustainability and resilience in supply chains is an active research issue. However, crisis logistics modeling with these factors for pharmaceutical products is rarely considered. In crises, perishable medicinal products such as drugs should be provided to hospitals at the lowest cost and expediently. This paper develops a new fuzzy robust stochastic model to deal with the crisis logistics of medicinal products by considering the dimensions of sustainability and resilience using multi-objective programming. Because this model contributes to the criteria of stability and flexibility. By defining three types of goals, this model seeks to find the optimal place to cover the demand when establishing field hospitals and the optimal route for transporting pharmaceutical products from the drug collection stands to the pharmacy, as well as the optimal route for transportation from the accident site to the field hospitals. Since the proposal is more complex than other pharmaceutical supply chain studies, to solve the model, a hybrid heuristic formulated by multi-choice objective programming is designed. The application of this model is indicated in a case study in Iran. The efficiency of the developed model is tested with sensitivities. The performance of the solution algorithm is analyzed with numerical results through quality and time measures. Finally, a discussion to evaluate the management insight of the solution of the proposed optimization model and the solution algorithm is concluded. The results indicate that the proposed algorithm reduces supply chain costs and dissatisfaction regarding the fairness of drug distribution and increases demand coverage.