Dynamic pricing to control loss systems with quality of service targets

A wide range of real time services can be modeled as loss systems. Numerous exam-ples arise in the service industry including: agent staffing for call centers, provisioning bandwidth for private line services, making rooms available for hotel reservations and congestion pricing for parking spaces. In general these services charge arriving cus-tomers a price for admission and customers expect a specific quality of service level. Given that arriving customers make their decision to join the system based on the cur-rent service price, the manager may use price as a mechanism to control the utilization of the system. A major objective for the manager is then to find a pricing policy that maximizes total revenue while meeting the quality of service targets desired by the customers. For systems with growing demand and service capacity, we provide a dynamic pricing algorithm. A key feature of our solution is congestion pricing. Our solution uses demand forecasts to anticipate future service congestion and set the present price accordingly. The optimal price is a function of the number of customers in the syste