Brownian networks are a class of linear stochastic control systems that arise as heavy traffic approximations in queuing theory. Such Brownian system models have been used to approximate problems of dynamic routing, dynamic sequencing and dynamic input control for queuing networks. A number of...

This paper considers a world in which pension funds may default, the cost of the associated risk of default is not borne fully by the sponsoring corporation, and there are differential tax effects. The focus is on ways in which the wealth of the shareholders of a corporation sponsoring a pension...

Motivated by applications in financial services, we consider a seller who offers prices sequentially to a stream of potential customers, observing either success or failure in each sales attempt. The parameters of the underlying demand model are initially unknown, so each price decision involves...

Generalizing earlier work on staffing and routing in telephone call centers, we consider a processing network model with large server pools and doubly stochastic input flows. In this model the processing of a job may involve several distinct operations. Alternative processing modes are also...

We consider a call center model with m input flows and r pools of agents; the m-vector \lambda of instantaneous arrival rates is allowed to be time dependent and to vary stochastically. Seeking to optimize the trade-off between personnel costs and abandonment penalties, we develop and illustrate...

Generalizing earlier work on staffing and routing in telephone call centers, we consider a processing network model with large server pools and doubly stochastic input flows. In this model the processing of a job may involve several distinct operations. Alternative processing modes are also...