Robust-possibilistic optimization method at design of a pharmaceutical supply chain network under uncertainty and discount on purchase the raw material

In this paper, a five-level pharmaceutical supply chain network is modeled under uncertainty. Levels of this pharmaceutical supply chain network include raw material supplier, production center, distribution center, Health centers and customers. Also, the objectives of this paper include minimizing the costs of the total supply chain network, minimizing the maximum unmet demand, and maximizing reliability in timely delivery of drugs, by considering the perishable time and the discount on the purchase of raw materials. Decision-making variables are divided into two strategic and tactical categories and, include determining the optimal number and location of potential facilities and determining the optimal amount of drug flow between the selected facilities, respectively. A robust-possibilistic optimization method has been used to control the uncertain parameters, and the hybrid LP-metric method and Monte Carlo simulation approaches have been used to solve the multi-objective model. Finally, by providing a numerical example, the outputs obtained from the solution of the model have been discussed.