An important supply chain research problem is the bullwhip effect caused by information distortion and variation amplification along a supply chain, which can lead to tremendous inefficiencies, such as excessive inventory investment and lost revenues. Motivated by engineering process control methods, this paper proposes a class of order-up-to policies and develops a nearly optimal policy to reduce the bullwhip effect. The proposed policy can significantly reduce the order variance while keeping the expected cost nearly optimal. According to our numerical studies, the order variance of the nearly optimal policy can be reduced by more than 50% while the expected cost is only slightly greater than that of the optimal policy derived in a paper by Lee et al. (1997).

Kwok-Leung Tsui is professor in the School of Industrial and Systems Engineering at Georgia Institute of Technology. He received his B.Sc. and M.Phil. from the Chinese University of Hong Kong, and Ph.D. in Statistics from the University of Wisconsin at Madison. He had worked in the Quality Assurance Center of AT&T Bell Laboratories before joining Georgia Tech in 1990.  
Dr. Tsui was a recipient of the 1992 NSF Young Investigator Award. He was the (elected) President and Vice President of the American Statistical Association Atlanta Chapter in 1992-1993. Dr. Tsui was the Chair of the INFORMS Section in Quality, Statistics, and Reliability (QSR) in 2000 and was the program chair of the QSR cluster sessions in 1999. He is a US representative in the ISO Technical Committee on Statistical Methods (TC 69) and a representative in the Southern Regional Council on Statistics.  
Dr. Tsui researches, teaches, and consults on statistical methods for quality improvement and supply chain management. His publications have appeared in Techometrics, J of Quality Technology, IIE Transactions, Int J of Production Research, among others.