【主讲】张哲美国西华盛顿大学决策科学系教授 加拿大西蒙·弗雷泽大学教师
【主题】随机需求与供应系统建模
【时间】6月20日(星期三)10:30-12:00
【地点】清华经管学院伟伦楼453室
【语言】中文
【主办】管理科学与工程系
【简介】
Zhe George Zhang
Dept. of Decision Sciences,
Western Washington University,WA,USA&
Faculty of Business Administration,
Simon FraserUniversity,BC,Canada
Part I: Service Systems:
Motivated by Flexible Staffing of the US-Canada Border Crossings
Abstract: In the first part of this research, we study waiting line
problems at the border-crossings between theU.S.andCanada. To
evaluate a practical staffing policy, we develop an analytical model to
compute the important performance measures. The policy is called
"congestion based staffing" or CBS, because the number of open
inspection booths is adjusted according to the queue length during each
planning period. Our analysis is based on the matrix-geometric solution,
the regeneration cycle, and the fluid approximations. With a certain
cost structure, we provide a numerical search approach to determine the
best CBS policy for border-crossing stations. Under certain conditions,
we can obtain the close-form solution for the optimal policy parameters
and prove the convexity of the average cost function.
Part II: Manufacturing Systems:
Apply the CBS model to Production/Inventory Systems
Abstract: In the second part of this research, we show that CBS model
can be applied to study a fixed number of production facilities
producing a specific type of items with random demand and production
time. The inventory policy is a base-stock (s, S) type with continuous
review. Some production facilities can be switched to producing other
secondary products if the inventory level is high and switched back when
the inventory level is slow. Under a cost structure which includes a
set-up cost, a linear holding cost, and a possible linear backorder
cost, an average cost function is developed. Using reasonable
approximation methods, we obtain the closed form formulas for computing
the optimal inventory and production policy. Excellent approximation
with high accuracy has been illustrated by extensive numerical analysis.
These easy-to-use formulas provide practitioners a useful tool in
determining the best inventory and production control policy under the
random demand and production time environment.