Dynamic Capacity Management with General Upgrading

Yueshan Yu (), Xin Chen () and Fuqiang Zhang ()
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Yueshan Yu: Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130
Xin Chen: Industrial Enterprise and Systems Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
Fuqiang Zhang: Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130

Operations Research, 2015, vol. 63, issue 6, 1372-1389

Abstract: This paper studies a capacity management problem with upgrading. A firm needs to procure multiple classes of capacities and then allocate the capacities to satisfy multiple classes of customers that arrive over time. A general upgrading rule is considered, i.e., unmet demand can be satisfied using multistep upgrade. No replenishment is allowed and the firm has to make the allocation decisions without observing future demand. We first characterize the structure of the optimal allocation policy, which consists of parallel allocation and then sequential rationing. Specifically, the firm first uses capacity to satisfy the same-class demand as much as possible, then considers possible upgrading decisions in a sequential manner. We also propose a heuristic based on certainty equivalence control to solve the problem. Numerical analysis shows that the heuristic is fast and delivers close-to-optimal profit for the firm. Finally, we conduct extensive numerical studies to derive insights into the problem. It is found that under the proposed heuristic, the value of using sophisticated multistep upgrading can be quite significant; however, using simple approximations for the initial capacity leads to negligible profit loss, which suggests that the firm’s profit is not sensitive to the initial capacity decision if the optimal upgrading policy is used.

Keywords: capacity management; inventory; upgrading; dynamic programming; revenue management (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (11)

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