The analysis of stochastic models is often greatly complicated if there are censored observations of the random variables. This paper characterizes families of distributions which help keep tractable the analysis of such models. Our primary motivation is to provide guidance to practitioners in...

A new criterion is introduced for comparing the convergence properties of variable metric algorithms, focusing on stepwise descent properties. This criterion is a bound on the rate of decrease in the function value at each iterative step (single-step convergence rate). Using this criterion as a...

A simple model is presented which allows us to determine the optimal size, fillup, and drawdown rates for a Strategic Petroleum Reserve (SPR) under a variety of supply and demand conditions. The optimal policy variables are determined by minimizing an analytic expression which we derive for the...

This part of the paper introduces some possible implementations of Self-Scaling Variable Metric algorithms based on the theory presented in Part I. These implementations are analyzed theoretically and discussed qualitatively. A special class of SSVM algorithms is introduced, which has the...

Typical queues do not have constant arrival rates. This paper discusses effective computational methods for dealing with queues having nonstationary arrival processes. It presents a computationally undemanding approximate method for finding the time dependent mean and standard deviation of the...