A large class of problems of sequential decision making under uncertainty, of which the underlying probability structure is a Markov process, can be modeled as stochastic dynamic programs (referred to, in general, as Markov decision problems or MDPs). However, the computational complexity of the...

In this paper we consider a singularly perturbed Markov decision process with finitely many states and actions and the limiting expected average reward criterion. We make no assumptions about the underlying ergodic structure. We present algorithms for the computation of a uniformly optimal...

In this paper we extend standard dynamic programming results for the risk sensitive optimal control of discrete time Markov chains to a new class of models. The state space is only finite, but now the assumptions about the Markov transition matrix are much less restrictive. Our results are then...

We consider the problem of control for continuous time stochastic hybrid systems in finite time horizon. The systems considered are nonlinear: the state evolution is a nonlinear function of both the control and the state. The control parameters change at discrete times according to an underlying...

We consider the problem of control for continuous time stochastic hybrid systems in finite time horizon. The systems considered are nonlinear: the state evolution is a nonlinear function of both the control and the state. The control parameters change at discrete times according to an underlying...

We address an assembly problem, motivated by flat panel display manufacturing, where the quality (or performance) of the final product depends upon characteristics of the components to be assembled, which are not constant from component to component. We analyze the tradeoff between the increase...

We consider a process control procedure with fixed sample sizes and sampling intervals, where the fraction defective is the quality variable of interest, a standard attributes control chart methodology. We show that relatively standard cost assumptions lead to formulation of the process control...

Thesis (Ph. D.)--University of Rochester. William E. Simon Graduate School of Business Administration, 2009.