Supply chain optimization with quantity discount policy under demand uncertainty

Quantity discount is the decision making of trade price between suppliers and manufacturers while the production is changeable due to the unknown demand in the real market. In this paper, the supply chain planning problem which considers the selection of the contracted suppliers, production quantity and inventory simultaneously is addressed. By considering those factors, the problem is formulated as a mixed integer nonlinear programming problem (MTNLP). We propose an outer approximation algorithm to solve the supply chain planning problems with quantity discount policy under demand uncertainty. Computational results show that the proposed method is effective for large scale problems compared with the conventional algorithm. The goal of research is to incorporate quantity discount policy into the mathematical model in order to help the decision making in the supply chain management.