Pricing computer services: queueing effects
Communications of the ACM
Optimal incentive-compatible priority pricing for the M/M/1 queue
Operations Research
User delay costs and internal pricing for a service facility
Management Science
Dynamic Pricing for Network Service: Equilibrium and Stability
Management Science
Congestion-dependent pricing of network services
IEEE/ACM Transactions on Networking (TON)
Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
IEEE/ACM Transactions on Networking (TON)
Dynamic Control of a Queue with Adjustable Service Rate
Operations Research
Analysis, Design, and Control of Queueing Systems
Operations Research
Optimal Pricing and Admission Control in a Queueing System with Periodically Varying Parameters
Queueing Systems: Theory and Applications
Operations Systems with Discretionary Task Completion
Management Science
Revenue Management of a Make-to-Stock Queue
Operations Research
Optimal buffer size for a stochastic processing network in heavy traffic
Queueing Systems: Theory and Applications
Admission control for a multi-server queue with abandonment
Queueing Systems: Theory and Applications
Dynamic admission and service rate control of a queue
Queueing Systems: Theory and Applications
Dynamic resource allocation in a multi-product make-to-stock production system
Queueing Systems: Theory and Applications
Power-aware speed scaling in processor sharing systems: Optimality and robustness
Performance Evaluation
Manufacturing & Service Operations Management
Optimal arrival rate and service rate control of multi-server queues
Queueing Systems: Theory and Applications
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We study a service facility in which the system manager dynamically controls the arrival and service rates to maximize the long-run average value generated. We initially consider a rate-setting problem where the service facility is modeled as an M/M/1 queue with adjustable arrival and service rates and solve this problem explicitly. Next, we use this solution to study a price-setting problem, where customers are utility maximizing and price- and delay-sensitive, and the system manager chooses state-dependent service rates and prices. We find that the optimal arrival rate is decreasing and the optimal service rate is increasing in the number of customers in the system; however, the optimal price need not be monotone. We also show that under the optimal policy, the service facility operates as one with a finite buffer. Finally, we study a numerical example to compare the social welfare achieved using a dynamic policy to that achieved using static policies and show the dynamic policy offers significant welfare gains.