The state of a system is modelled by Brownian motion with negative drift and an absorbing barrier at the origin. A repairman arrives according to a Poisson process of rate λ. If the state of the system at arrival of the repairman does not exceed a certain threshold, he/she increases it by a random amount, otherwise no action is taken. Costs are assigned to each visit of the repairman, to each repair, and to the system being in state 0. It is shown that there exists a unique arrival rate λ which minimizes the average cost per unit time over an infinite horizon.

Interconnections between occurrence times of nonhomogeneous Poisson processes, record values, minimal repair times, and the relevation transform are explained. A number of properties of the distributions of occurrence times and interoccurrence times of a nonhomogeneous Poisson process are proved when the mean-value function of the process is convex, starshaped, or superadditive. The same results hold for upper record values of independently identically distributed random variables from IFR, IFRA, and NBU distributions.

We show that the calculation of the infinite-horizon value function for a linear/quadratic Markov decision process by policy improvement is exactly equivalent to solution of the equilibrium Riccati equation by the Newton-Raphson method. The assertion extends to risk-sensitive and non-Markov forinulations and thus shows, for example, that the Newton-Raphson method provides an iterative algorithm for the canonical factorization of operators which shows second-order convergence and has a variational basis.

We consider a K-out-of-N system maintained by R repairmen, where the lifetime of the ith component is an exponentially distributed random variable with parameter μi. Repairmen are distinguishable, and the time it takes the rth repairman to repair a failed component is an exponentially distributed random variable with parameter λr. Repaired components are as good as new and preemptions are allowed. We show that the policy that assigns the faster repairmen to the most reliable components is optimal with respect to several optimality criteria.

The approach we take in establishing stochastic optimality with respect to the number of functioning components is of wide applicability to different classes of stochastic optimization problems.

The Coxian-2 distribution is a very useful distribution for queuing and reliability analysis. It is important to know when a general probability distribution can be approximated by a Coxian-2 distribution by fitting the first three moments. For a positive random variable with a squared coefficient of variation larger than 1, a lower bound on its third moment is known for which a three-moment fit exists. To complete the figure, in this note lower and upper bounds on the third moment are derived when the squared coefficient of variation is between 0.5 and 1. Also, we characterize the C2-distributions that correspond to these bounds.

A new partial ordering generated by the set of star-shaped functions is introduced. This ordering is equivalent to the stochastic comparison of the length-biased distributions which are frequently appropriate for certain natural sampling plans in biometry, reliability, and survival analysis studies. It is shown that the length-biased ordering fits in the framework of stochastic and variatiility orderings. It enjoys many properties similar to those of the stochastic and variability orderings.

A consecutive-k−out−of−n system is a graph with n vertices where the system fails if and only if some path of k consecutive vertices all fail. The assumption is made that qi, is the failing probability of the ith vertex and the states of the vertices are statistically independent. The problem is to find the best system, i.e., a set {q1, …,qn}, and its assignment to the vertices of the system graph that maximizes the reliability of the system, under the constraint that the product of qi's is a constant. We solve the problem for all lines and some cycles. We then extend our results to trees and show that for given n and k the best tree is a star and the worst is a line.

An infinite dam with discrete inputs arriving at times 0 = T0 < T1 <…< Tn <… is considered, where {Tn;n = 0,1,2,…} forms a renewal process. There is a random release from the dam during the interrenewal times which depends on the content as well as on the length of the time after the last input. A relation is derived that connects the content distribution at any time t to that when t is a renewal point. This relation is used to obtain the content distribution in the limiting case and in the transient case. The probability of emptiness is obtained and an integral equation is derived for the probability of first emptiness in a special case.

We study a model of queue storage in which items (requests for single units of storage) arrive in a Poisson stream and are accommodated by the first available location in a linear scan of storage. The processing times of items are independent, exponentially distributed random variables. The set of occupied locations (identified by their indices) at time t forms a random subset Si, of [1,2,.…]. The extent of the fragmentation in Si, i.e., the alternating holes and occupied regions of storage, is measured by Wt, = max St, – |St|.

The materials-loss problem is examined under the assumption that one wishes to minimize the maximum expected amount of material diverted. A solution is obtained in the case of constant diversion under a simple sequential probability ratio test (SPRT). Extensions to the cases of correlated errors, random diversion schemes, and the Page and Shirayev-Roberts tests are examined. A thought-provoking application to the regulation of strategic special nuclear materials is given.

We introduce in this paper a new measure of component importance, called redundancy importance, in coherent systems. It is a measure of importance for the situation in which an active redundancy is to be made in a coherent system. This measure of component importance is compared with both the (Birnbaum) reliability importance and the structural importance of a component in a coherent system. Various models of component redundancy are studied, with particular reference to k/out / of / n systems, parallel-series systems, and series-parallel systems.

N tasks must be successfully performed for a job to be completed. The tasks may be attempted in any order, where each attempt of task i requires an expected cost ci and is successful with probability pi. Whenever an attempt fails, the job is fed back to the initial stage and the entire sequence starts again. We show that the cost of completing a job is minimized if the tasks are sequenced via increasing values of ci/(l–pi). We further show that the same result holds when the feedback can be either to stage i itself or to the starting task.

Systems are studied that consist of interfering components which are alternatively active (busy) and passive (idle) for random periods. Such systems naturally arise from the performance evaluation of computer models. A concrete invariance condition is imposed on the interferences allowed. Under this condition, the steady-state vector of active components is shown to be of product form as well as to be robust to distributional forms of active and passive periods. The proof is simple and self-contained. A number of concrete and generic examples is provided. These include resource sharing mechanisms, hierarchical circuit switchings, parallel processing, priorities, and breakdowns.

In [1] an approach to approximate the transition probabilities and mean occupation times of a continuous-time Markov chain is presented. For the chain under consideration, let Pij(t) and Tij(t) denote respectively the probability that it is in state j at time t, and the total time spent in j by time t, in both cases conditional on the chain starting in state i. Also, let Y1,…, Yn be independent exponential random variables each with rate λ = n/t, which are also independent of the Markov chain.

Simultaneous estimation problems that deal with the estimation of several means for normal distributions are considered under the squared-error loss. Heuristic procedures are presented which can be applied to parameter estimation problems for a wide class of distributions specified only by their means and variances. Explicit results are obtained for the heuristic shrinkage estimators in the normal distribution case. Limiting behavior of the relative risk savings of these estimators is studied. The performances of the proposed estimators for normal distribution means are compared with other existing estimators by a computer simulation.

When confronted by a sequence of independent, identical, favorable-though- risky investments, a risk-averse agent will in fact elect to invest as part of a large syndicate even if he or she would not undertake even one of the investments by himself or herself. This willingness to invest emanates from the risk reduction associated with the risk pooling effected by the syndicate. Our first two theorems describe the syndicate size needed to induce the agent's participation.

The consequence of adding risks is considered next. We demonstrate that the agent will undertake a large number of these independent investments by himself or herself even if each investment taken by itself constitutes a poor risk. The conditions needed to ensure this somewhat surprising result are (a) moment bounds on the investments, and (b) either a polynomial or an exponential bound on the lower tail of the agent's utility function. Finally, we draw the connection between this result, proper risk aversion, and monotonicity of the agent's absolute aversion to risk.

Analysis of the initial transient problem of Monte Carlo steady-state simulation motivates the following question for Markov chains: when does there exist a deterministic Tsuch that P{X(T) = y|(0) = x} = ®(y), where ρ is the stationary distribution of X? We show that this can essentially never happen for a continuous-time Markov chain; in discrete time, such processes are i.i.d. provided the transition matrix is diagonalizable.