Optimal two ordering policy with censored demand information in a quick response (QR) system

This paper investigates the optimal two ordering policy regarding censored demand information in a quick response (QR) system, which generalizes the conventional information updates issues in a real-life setting. Firstly, the optimal two ordering issue is modeled and formulated, and an explicit expected profit objective is presented; secondly, the existence of the optimal solution is analyzed. Thirdly, a straightforward sample-based algorithm is developed to solve the optimal solution, and a numerical example is provided to illustrate practical usage of our research. Further, the comparison between the model in which censored demand information is considered and that in which the censored demand information is neglected; and some managerial insights are proposed to help practitioners to treat censored information setting correctly. The results show that the model with censored demand information can reveal the "real" optimal ordering decisions and increase the expected profit.