While batch processes are ubiquitous across industries, there is little understanding of the determination of the capacity (i.e., the maximum long-term output rate) of such processes. In this paper, we consider processes with collaboration (activities may require multiple resources...

In many practical settings, learning algorithms can take a substantial amount of time to converge, thereby raising the need to understand the role of discounting in learning. We illustrate the impact of discounting on the performance of learning algorithms by examining two classic and...

In many real-world applications, there is a growing trend to supplement reserved capacity with on-demand capacity; examples include the deployment of customer-service agents by call centers, servers by cloud-computing providers, and health-care professionals by post-acute-care services. We...