Optimal investment in product-flexible manufacturing capacity
Management Science
Airline seat allocation with multiple nested fare classes
Operations Research
Principles on the benefits of manufacturing process flexibility
Management Science
An optimal policy for a two depot inventory problem with stock transfer
Management Science
Investment Strategies for Flexible Resources
Management Science
Airline Yield Management with Overbooking, Cancellations, and No-Shows
Transportation Science
Revenue Management: Research Overview and Prospects
Transportation Science
Single-Period Multiproduct Inventory Models with Substitution
Operations Research
A Dynamic Model for Airline Seat Allocation with Passenger Diversion and No-Shows
Transportation Science
Assessing the Benefits of Different Stock-Allocation Policies for a Make-to-Stock Production System
Manufacturing & Service Operations Management
Newsvendor Networks: Inventory Management and Capacity Investment with Discretionary Activities
Manufacturing & Service Operations Management
Optimal Stock Allocation for a Capacitated Supply System
Management Science
Stock Rationing in an M/Ek/1 Make-to-Stock Queue
Management Science
A New Decision Rule for Lateral Transshipments in Inventory Systems
Management Science
Commissioned Paper: Capacity Management, Investment, and Hedging: Review and Recent Developments
Manufacturing & Service Operations Management
Optimal Policies for Inventory Systems with Priority Demand Classes
Operations Research
Overbooking with Substitutable Inventory Classes
Operations Research
Capacity Management in Rental Businesses with Two Customer Bases
Operations Research
Pricing and Operational Recourse in Coproduction Systems
Management Science
An Improved Dynamic Programming Decomposition Approach for Network Revenue Management
Manufacturing & Service Operations Management
Computers & Mathematics with Applications
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We examine a multiperiod capacity allocation model with upgrading. There are multiple product types, corresponding to multiple classes of demand, and the firm purchases capacity of each product before the first period. Within each period, after demand arrives, products are allocated to customers. Customers who arrive to find that their product has been depleted can be upgraded by at most one level. We show that the optimal allocation policy is a simple two-step algorithm: First, use any available capacity to satisfy same-class demand, and then upgrade customers until capacity reaches a protection limit, so that in the second step the higher-level capacity is rationed. We show that these results hold both when all capacity is salvaged at the end of the last demand period as well as when capacity can be replenished (in the latter case, an order-up-to policy is optimal for replenishment). Although finding the optimal protection limits is computationally intensive, we describe bounds for the optimal protection limits that take little effort to compute and can be used to effectively solve large problems. Using these heuristics, we examine numerically the relative value of strictly optimal capacity and dynamic rationing, the value of perfect demand information, and the impact of demand and economic parameters on the value of optimal substitution.