This paper presents a dynamic programming (DP) model of an electric utility's optimal policy for operating a nuclear power plant (NPP). The utility chooses the level of capacity utilization of the NPP as a function of signals about the NPP's current operating state. In each period the utility...

A pervasive concern with the use of self-reported health and disability measures in behavioral models is that they are biased and endogenous. A commonly suggested explanation is that survey respondents exaggerate the severity of health problems and incidence of disabilities in order to...

The authors present an empirical model of optimal operation of nuclear power plants. The optimal lifetime is the solution to an optimal stopping problem: the plant is closed when the expected discounted losses from continued operation exceed the discounted costs of decommissioning. The authors...

This paper analyzes the asymptotic convergence properties of policy iteration in a class of stationary, infinite-horizon Markovian decision problems that arise in optimal growth theory. These problems have continuous state and control variables, and must therefore be discretized in order to...

In many dynamic programming problems, a mix of state variables exists - some exhibiting stochastic cycles and others having deterministic cycles. We derive a formula for the value function in infinite-horizon, stationary, Markovian decision problems by exploiting a special partitioned-circulant...

This paper formulates a simple, regenerative, optimal-stopping model of bus-eng ine replacement to describe the behavior of Harold Zurcher, superinte ndent of maintenance at the Madison (Wisconsin) Metropolitan Bus Comp any. Admittedly, few people are likely to take particular interest in Harold...