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*************************** Special Date ******************************
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Seminar
             Department
of Systems Engineering and Engineering Management 
                                 
The Chinese 
  
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| Title | : | Inventory Rationing for
  Multiple Class Demand under Continuous Review | 
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| Speaker | : | Prof. Qing Ding | 
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| Date | : | August 8th, 2007 (Wednesday) | 
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| Time | : | 4:30 p.m. - 5:30 p.m. | 
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| Venue | : | Room 513 | 
|   |   | William M.W. Mong Engineering Building | 
|   |   | (Engineering Building Complex Phase 2) | 
|   |   | CUHK | 
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Abstract:
 
| We consider the problem of purchasing inventory from a
  supplier and rationing it to multiple demand classes in a continuous review
  environment. Each demand class is characterized by a demand rate and a
  contribution margin per unit filled. Further, customer classes are
  distinguished by the likelihood they will wait for fulfillment. The firm must
  also determine if to serve a demand when it arrives or if it is to be placed
  on back order. The firm must also determine when it should place an order
  from its supplier. We assume Poisson demand, a fixed setup cost for orders to
  the firm’s supplier and partial, class-dependent demand backordering. The problem of allocating inventory to multiple demand
  classes has been investigated in many settings. In fact, the revenue/yield
  management literature is based on determining which demands to satisfy at
  what prices. However, much of this work focuses on perishable inventory and
  single period models. Within the non-perishable inventory, multiple period
  models, the literature considers the periodic review polices or the
  continuous review heuristics. The current paper contributes to the literature
  by providing a polynomial-time, epsilon-optimal algorithm that maximizes the
  revenue less inventory holding and backorder costs for a multiple class
  problem with setup costs and zero lead time.  The problem is solved by defining a suitable dynamic
  program that uses an initial profit rate to find an allocation and ordering
  policy. The resulting policy then defines an expected profit rate. By
  comparing the initial and resulting rates, the algorithm adjusts its search
  and approaches the optimal, feasible expected profit rate through a
  tatonnement-like process. | 
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Biography:
 
| Qing DING is an Assistant Professor of Operations
  Management at the  | 
************************* ALL ARE WELCOME ************************
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| Host | : | Prof. Houmin Yan | 
| Tel | : | (852) 2609-8329 | 
| Email | : | |
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| Enquiries | : | Lu Qin or
  Jeffrey Xu Yu | 
|   | : | Department of Systems Engineering and Engineering
  Management | 
|   |   | CUHK | 
| Website | : | |
| Email | : | |
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