Optimal production and inventory policies of priority and price-differentiated customers

Duran S., LİU T., SİMCHİ-LEVİ D., Swann J. L.

IIE TRANSACTIONS, vol.39, no.9, pp.845-861, 2007 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 39 Issue: 9
  • Publication Date: 2007
  • Doi Number: 10.1080/07408170600972982
  • Journal Name: IIE TRANSACTIONS
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.845-861
  • Keywords: inventory policy, tactical inventory, customer differentiation, threshold policies, two-class, priority differentiated, price differentiated, DEMAND CLASSES, LOST SALES, RATIONING POLICIES, MODEL, SYSTEMS


Many firms are exploring production and supply chain strategies when customers may be segmented into different classes based on service level or priority. Such segmentation can result in a more efficient production system as well as a better match between supply and demand. In this research, we analyze a system with customer classes 1 and 2, where customer class 1 has a higher priority of fulfillment than customer class 2 in the same period. We develop an optimal production and inventory strategy that rations current and future limited capacity between customer classes 1 and 2, through reserving inventory for the future and accepting orders now for future delivery when demand and production are general stochastic functions. We show that a modified order-up-to policy ( S*, R-i*, B-i*) is optimal in each period. S* is the targeted inventory level after production at the beginning of the period; R-1* represents the optimal inventory to be protected from being sold to both classes, and R-2* is the additional amount of inventory to protect from class 2. B-2* is the optimal amount of future capacity to make available to both classes through backlogging, and B-1* is the additional backlogging amount for class 1. Computational analysis shows that the differentiation strategy can result in a significant profit improvement over a traditional inventory policy.