Fast-moving consumer goods network design with pricing policy in an uncertain environment with correlated demands. (March 2021) - Nasiri, G. Reza; Kalantari, Mohammad; Karimi, Behrooz
Highlights: A mixed-integer non-linear programming model is developed in an uncertain environment. Considered decisions are pricing, facility location and inventory strategy. The considered supply chain includes dual sales channels to control demand leakage. The considered market includes complementary or substitute products to determine the optimal price. A heuristic approach (a linear regression) is provided to forecast demand for correlated products. Abstract: Facility location is one of the most important strategic decisions in designing a supply chain network. However, given the interaction of strategic decisions on tactical and operational decisions, it seems necessary to provide models that integrate these decisions. In this study, a mixed-integer non-linear programming model is developed to determine the optimal pricing of products in different sales and distribution channels while integrating location-allocation decisions and inventory control of distribution centers in an uncertain environment. In order to provide a more realistic model, it is assumed that there is a correlation between demands for products, which poses a critical challenge for modeling and pricing. A Memetic algorithm is used to solve the mixed-integer nonlinear programming model. The implementation results of the designed sample problems show the good performance of the proposed algorithm.