Stochastic Bilevel Programing to Design of A JIT Pharmaceutical Supply Chain Network: Modeling and Algorithm

In the pharmaceutical supply chain, pharmaceutical products must be distributed among consumers with good quality at the right time and in the right place. Medicineis a product which affects the health of society and its timely delivery to consumers is of great importance. Therefore, it requires proper planning for its production and distribution. In this paper, we developed a model that minimize the cost of production, inventory, delivery, earliness and tardiness. We also assumed the uncertainty of demand and solved the linear mathematical model using stochastic programming and we solved the problem with stochastic programming. Also, due to the fact that the model with the objective function of earliness and tardiness with different delivery times of NP-hard problem for this problem, a hybrid genetic and variable neighborhood search algorithm were presented. Here, five scenarios were considered, the expected value of perfect information (EVPI) was measured and the obtained results were compared with the two-stage random-scheduling model. The computational results showed the efficiency of the developed model. Also, the results of the proposed hybrid algorithm were compared with the genetic algorithm, and the results showed that in terms of objective function, the hybrid algorithm has a much better performance compared to the genetic algorithm.