Developing an Optimal Policy for Green Supplier Selection and Order Allocation Using Dynamic Programming

Supplier selection is one of the critical issues in the supply chain. Green supplier selection is performed based on the assessment of quantitative and qualitative criteria in two fields including economic and environmental attributes. In this study, a two-level supply chain model has been proposed for green supplier selection and order allocation in a multiperiod and single-product environment. In the first phase, the analytic hierarchical process (AHP) method is used to rank the suppliers and in the second phase, a model is designed based on constraints such as demand, capacity, and allowed level of inventory and shortage to maximize the total value of purchase (TVP) and total profit of purchase (TPP). Demand is assumed to be stochastic in different periods. Thus random demand leads to create various scenarios in the planning horizon. A new integrated approach is presented based on stochastic programming and dynamic programming to solve the problem. The incorporation of stochastic demand condition and application of dynamic programming is a novel idea. Finally, a numerical example is provided to investigate the procedure in details.