Designing a flexible supply chain network in the pharmaceutical industry with different delivery modes

With the increase of competition in the work environment, organizations and manufacturing plants have been forced to optimize their supply chain in order to ensure the efficiency of operations. Optimization helps to reduce costs and increase customer satisfaction. The main element of the chain is the transport network, which determines the efficiency. This element is used in all stages of production, from production to delivery of the final product to customers. Also, by having a flexible supply chain network, which is one of the competitive strategies, it is possible to cover uncertain situations, a large variety of products, and responding to changes in demand and in time. Flexible supply chain networks are one of the most influential classes of the supply chain in production and service. In such networks, different delivery modes can significantly increase the efficiency of the entire chain. In this article, mixed integer programming has been used to design four-stage and multi-product supply chain networks in the pharmaceutical industry. The introduced model includes three different modes of delivery, which are: normal delivery, direct transportation, and direct delivery. Due to the complexity of this problem, meta-heuristic models have been used, in order to answer these goals, 10 adaptive and classical meta-heuristic algorithms have been developed and a random experiment has been conducted in order to measure the parameters more accurately. After the parameter setting stage, the final test is presented on the issues generated by the pharmaceutical industry. The obtained results show that the vibration-damping optimization algorithm is better than the other proposed algorithms.