Dynamic real-time order promising and fulfillment for make-to-order company in supply chain environment (ID: 1-032)

Recently, rapid response to customer requirement and flexibility to handle uncertainties in both demand and supply are becoming more and more important for make-to-order companies in supply chain environment. In order to meet these challenges, a dynamic control architecture that monitors real-time order and factory data, and continuously project and updates a view of future business process was proposed. The real-time ATP (Available-to-Promise) models facing dynamic order arrivals are primarily deterministic and static MIP (Mixed Integer Program) models. Real-time decisions were made based on the real-time data monitoring function by MDP (Markov Decision Process) model using an underlying simulation model of the supply chain to generate state transitions. The research incorporating real-time data for realizing dynamic order promising and fulfillment can lead to increased profitability and improved customer service.