A Multi-objective Stochastic Programming Model for Order Quantity Allocation under Supply Uncertainty

Abstract

One of the basic and significant subjects in supply chain management is purchasing and supply management, in which supplier selection and order allocation occupy the critical position. Recently, it has been shown that supply uncertainty is of great concern to supply chain managers and practitioners. In this paper, by taking the constraints of minimum purchasing quota and minimum production batch into account, a multi-objective mixed-integer stochastic programming model considering uncertainty in both supply timing and quantity is presented. By means of transforming the stochastic constraints into deterministic equivalents, the model is converted into a linear programming model. An improved two-phase heuristic approach is proposed and its feasibility and efficiency is illustrated through a numerical example. Further, another numerical instance is conducted to evaluate the effects of the weight of each objective and uncertainty degree on the optimal order policy and to obtain some managerial insights for the decision-making of the manufacturers.