Prof. Hanqin Zhang
National University of Singapore/Chinese Academy of Science
Talk:
Optimal Policies for Assemble-to-Order N-system
Abstract:
In this talk we consider component replenishment policy and common component allocation rule in N-system with positive leadtimes. By the sample-path decomposition and the linear program lower-bound techniques, and with the symmetric cost assumption, we show: (i) Among all feasible replenishment policies, No-Holdback-Policy as common-component allocation rule is optimal; (ii) For identical components leadtimes, the base-stock policy is an optimal replenishment policy; (iii) For nonidentical leadtimes, the optimal replenishment policy is of coordinated base-stock. At the same time, we also discuss how system-parameters, such as demand rates and leadtimes, affect optimal replenishment policy and average cost.
This is a joint work with Lijian Lu and Jeanette Song
Biography:
Dr. Hanqin Zhang is a professor of Operations Research at Academy of Mathematics and Systems Science, Chinese Academy of Sciences (CAS). He has held visiting position at National University of Singapore, University of Texas at Dallas, Chinese University of Hong Kong. Dr Zhang received his Ph.D. in Operations Research at Institute of Applied Mathematics, CAS in 1991, and was a postdoctoral fellow at Marburg University (Germany), University of British Columbia, and Toronto University (Canada). His main research interests are queueing network theory, supply chain management, stochastic manufacturing systems, and applied probability. Dr Zhang has published in leading international operations research and applied probability journals such as Operations Research, Manufacturing and Service Operations Management, Productions and Operations management, Mathematics of Operations Research, Annals of Applied Probability. He coauthored two books on supply chain management and stochastic manufacturing systems. He received Academic Excellence Award for One-Hundred Talents Program of CAS, and Distinguished Young Investigator Grant (China).
