pharmasiuticals can be considered a strategic commodity that is related to the health of people and society and its role in health systems is increasing day by day. Supply chain network design as one of the most important subsets of strategic decision making in supply chain management has an important role in the economic performance of the pharmasiutical supply chain. In this research, a multi-objective mixed integer linear programming model has been developed to design a forward/reverse pharmasiutical supply chain network that is realistic and close to reality. The goal of this model is to simultaneously reduce the costs of the entire chain (economic) and environmental pollution (environmental) and increase employment (social). Strategic decisions such as determining the location of the centers as well as some tactical decisions, such as the optimal flow of products and inventory maintenance of each product family are made by the proposed model. The center of gravity approach has been used to deal with the fuzzy uncertainty in the demand and return data. As a case study, Iran and its 31 provinces have been considered as demand points and according to the data collected from relevant organizations, the multi-objective model presented with GAMS and MATLAB software has been solved. To solve the model, four multi-objective decision-making methods have been used, namely Epsilon constraint methods, weighted LP-metric, non-dominated sorting genetics and imperialist competitive. The reason for using meta-heuristic multi-objective algorithms is the high execution time of the model with multi-objective algorithms for accurate solution. To implement the model and eva‎luate the solution methods, thirty numerical examples in small, medium and large dimensions are considered. Comparison of numerical results shows that meta-heuristic algorithms have a good performance to solve the proposed model. By comparing the two meta-heuristic algorithms, it was found that the non-dominated sorting genetics algorithm has better performance in three response quality indicators and in one performance index worse than the imperialist competitive algorithm. Using this model in the design and implementation of the pharmasiutical chain can help relevant managers in strategic and tactical decisions and assist them in the existing competitive environment in terms of economic and executive.

علي شاهنده نوك آبادي

مهدي مهنام

رضا حجازي، مهدي علينقيان