A genetic-algorithm-based approach to the two echelon pharmaceutical inventory system

The two-echelon supply chain model consists of two separate members with different goals. In this study, the studied supply chain is considered a two-echelon supply chain comprising a supplier, a retailer, and one of drug. At the same time, the effects of the components of the two-echelon model on profit were investigated. This problem aims to maximize the total profit generated during sale and distribution of the product. Sales take place at the drug retailer, and order periods are determined according to the frequency of visits of the drug supplier. With this visit frequency in mind, the pharmaceutical retailer follows a periodic review inventory model. In the system, the decision variable for the retailer is the safety factor that affects the profitability of the pharmaceutical supplier, according to the order level. The decision variables for the supplier are the frequency of visits, the number of replenishments, and the delivery time. In this study, four different models have been applied: the decentralized model, the centralized model, the economic cooperation model, and the social cooperation model. By defining new variables, four different scenarios were created for each model. These scenarios were observed in four different test problems. The models were solved using a genetic algorithm, and the results were compared in terms of profitability. According to the research findings, the heuristic model of the two-echelon pharmaceutical supply chain problem provided greater profitability for both echelons in the chain. This study also showed that the Genetic Algorithm gives better results than the traditional solution applied to a similar problem in the literature.