Department of Industrial Engineering and Management
National Chiao Tung University, Taiwan
1001 Ta Hsueh Road, Hsinchu, Taiwan 300, ROC
Department of Industrial Engineering and Engineering Management
National Tsing Hua University, Taiwan
101, Section 2 Kuang Fu Road, Hsinchu, Taiwan 30013, Republic of China
This study used Markov modulated Poisson process (MMPP) to model supply systems under various uncertainty constraints. First the uncertainty factors embedded in a supply system were assumed to be unreliable server with or without unreliable repairman. The market demand may be non-stationary random process. Steady state performance measures under different uncertainty scenarios were investigated by using an algorithmic procedure to solve the underlying quasi-birth-and-death (QBD) process. The optimal resource design of the supply systems under various uncertainty constraints was then solved as the trade-off among costs of inventory holding, customer waiting, server repair and normal operation. Numerical studies of the proposed models investigated the impact of uncertainties on the performance of a multi-echelon supply system under a make-to-order (MTO) supply policy. The results are satisfactory and provide managerial insights on strategic supply decision.
Keywords: Markov modulated Poisson process, quasi-birth-and-death, supply system
(*Contact: E-mail frank.iem88g@nctu.edu.tw )
Cite this article as: Fong-Fan Wang and Chao-Ton Su , "Supply System Design under Uncertainty Constraint by Using Markov Modulated Poisson Process Modeling ," Journal of the Chinese Institute of Industrial Engineers, 23, 20-33 (2006).