Abstract
This article focuses on the strategic issue of an agile supply chain. Different goals are considered in supply chain design. Today, the concept of sustainability in supply chains plays an important role in goal setting. In general, sustainability leads to less economic, social, and environmental risks, and attention to this type of sustainability covers many criteria in the literature. Therefore, in this study, optimization of the stability of a supply chain network has been considered. In addition, a lesser-known aspect of sustainability, the political aspect, has been added to the previous aspects. This paper assumes four levels, namely supplier, wholesaler, retailer, and customer. An optimal network structure is designed to consider economic, social, and environmental sustainability and the new measure of political sustainability. The design of this supply chain is done by defining a mathematical model that has several objective functions, including economic, political, and environmental goals. These objective functions select the relationships and links between the levels in a supply chain network. For this purpose, a directional graph corresponding to a supply chain is designed. Then, with the help of an ideal multi-objective planning problem, an optimal configuration is obtained, which is a subgraph of the main network graph. The target problem has been modeled for a holding company which is a supply chain for COVID-19 drugs. Then, problem is solved using Multi-objective Particle Swarm Optimization (MOPSO) metaheuristics algorithm and NSGAII multi-objective genetic algorithm. A comparison was carried out between these two methods, and the results indicated that MOPSO performed better. The value of the objective functions is calculated, and the best value for the considered functions is obtained. Also, the amount of drug supply has been obtained by two distributors. Also, the amount of medicine purchased by the customer from each pharmacy is determined.