Management Science
Dynamic scheduling in multiclass queueing networks: Stability under discrete-review policies
Queueing Systems: Theory and Applications
Queueing Systems: Theory and Applications
Optimal Leadtime Differentiation via Diffusion Approximations
Operations Research
Optimal Control of a High-Volume Assemble-to-Order System
Mathematics of Operations Research
Dynamic Control of a Multiclass Queue with Thin Arrival Streams
Operations Research
Reliable Due-Date Setting in a Capacitated MTO System with Two Customer Classes
Operations Research
Queueing Systems: Theory and Applications
Dynamic Pricing and Lead-Time Quotation for a Multiclass Make-to-Order Queue
Management Science
Dynamic Control of a Make-to-Order, Parallel-Server System with Cancellations
Operations Research
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We consider a congestible system serving multiple classes of customers who differ in their delay sensitivity and valuation of service or product. Customers are endowed with convex-concave delay cost functions. A system manager offers a menu of lead times and corresponding prices to arriving customers, who then choose the lead-time--price pair that maximizes their net utility value minus disutility of delay and price. We investigate how such menus should be chosen dynamically depending on the system backlog to maximize welfare. We formulate a novel fluid model of the problem and show that the cost-balancing policy based on the convex hulls of the delay cost functions is socially optimal if the system manager can tell customer types apart. If types are indistinguishable to the system manager, the cost-balancing policy is also incentive compatible under social optimization. Finally, we show through a simulation study that the cost-balancing policy does well in the context of the original stochastic problem by testing it against various natural benchmarks.