A stochastic theory of the firm
Mathematics of Operations Research
Monotone control of queueing networks
Queueing Systems: Theory and Applications
How does the value function of a Markov decision process depend on the transition probabilities?
Mathematics of Operations Research
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Structural results for the control of queueing systems using event-based dynamic programming
Queueing Systems: Theory and Applications
The Underlying Markov Decision Process in the Single-Leg Airline Yield-Management Problem
Transportation Science
Structural Properties of Stochastic Dynamic Programs
Operations Research
Optimal Stock Allocation for a Capacitated Supply System
Management Science
Optimal Pricing and Admission Control in a Queueing System with Periodically Varying Parameters
Queueing Systems: Theory and Applications
Capacity Management in Rental Businesses with Two Customer Bases
Operations Research
Monotonicity in Markov Reward and Decision Chains: Theory and Applications
Foundations and Trends® in Stochastic Systems
Optimal pricing and production policies of a make-to-stock system with fluctuating demand
Probability in the Engineering and Informational Sciences
Pricing and Capacity Rationing for Rentals with Uncertain Durations
Management Science
Admission control with batch arrivals
Operations Research Letters
Admission control for a multi-server queue with abandonment
Queueing Systems: Theory and Applications
Dynamic pricing and scheduling in a multi-class single-server queueing system
Queueing Systems: Theory and Applications
Optimal control of a production-inventory system with customer impatience
Operations Research Letters
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This paper studies a class of queueing control problems involving commonly used control mechanisms such as admission control and pricing. It is well established that in a number of these problems, there is an optimal policy that can be described by a few parameters. From a design point of view, it is useful to understand how such an optimal policy varies with changes in system parameters. We present a general framework to investigate the policy implications of the changes in system parameters by using event-based dynamic programming. In this framework, the control model is represented by a number of common operators, and the effect of system parameters on the structured optimal policy is analyzed for each individual operator. Whenever a queueing control problem can be modeled by these operators, the effects of system parameters on the optimal policy follow from this analysis.