Supply chain network design using trade credit and bank credit: A robust optimization model with real world application. (November 2018) - Alavi, Seyyed Hossein; Jabbarzadeh, Armin
Highlights: We formulate a stochastic robust optimization model for the optimal design of supply chain networks. The financing sources of trade credit and bank credit are incorporated into the supply chain network design model. We develop a solution algorithm based on Lagrangian relaxation approach. The application of the proposed methodology is investigated in an actual supply chain. We derive important insights from tradeoff between solution robustness and model robustness. Abstract: Financing is of paramount importance to supply chains. This paper presents a stochastic robust optimization model for supply chain network design problem, while accounting for financial resources of trade credit and bank credit. The robust model can assist in determining the number and location of facilities as well as financing decisions. The objective is to maximize expected supply chain profit under demand uncertainty. A solution method based on the Lagrangian relaxation technique is developed to solve the model. The application of the proposed approach is investigated using an empirical case study. The obtained numerical results arrive at important managerial insights.