Joint decisions in order quantity determination and pricing under uncertain environment

Effective management of interfaces between procurement, supply, production and distribution as a whole towards higher efficiency of supply chain is an important issue in implementing supply chain management (SCM). In this paper, coordination between supplier and buyers in a distribution system with one supplier and multiple heterogeneous buyers under uncertain environment are focused, where the supplier as a manufacturer admits orders in production period, and the buyers may be distributed in different regions with individual and distinctive order cycles. The average inventory holding costs at the supplier is viewed upon as a function of order schedule rather than constant, and is taken into account in the supplier's operation cost formula. Acting as leader, the supplier schedules orders to synchronize production cycle, and then determines order quantities and production quantity simultaneously via quantity discounts to minimize his operation cost without decrease buyer's gain so as to encourage buyer to increase his order quantity. A feasible two-stage-order (TSO) schedule for orders is proposed and some properties are discussed in this paper. A common discrete all-unit quantity discount schedule with many break points is used. In view of uncertain demands, we explored the cooperation under uncertain environment, and improved fuzzy chance constrained programming model, which can be used to set reasonable quantities and discounts plan by supplier to share the venture of buyers for uncertain demands. After formulating the model, we first analyze buyers' responses to this general discrete quantity discount schedule, and find that it doesn't make buyers' costs decreased evidently. In order to arrive Win-Win fashion, second discount is advanced to share benefits more equitable without increasing complexity of model. The applicability of this research is to help modern manufacturing enterprises and logistics-oriented service enterprises implementing SCM. Algorithms are designed and the simulation experiments are conducted.