Sensitivity analysis represents an important aspect of network flow design problems. For example, what is the incremental increase in system flow of increasing the diameters of specified pipes in a water distribution network? Although methods exist for solving this problem in the deterministic case, no comparable methodology has been available when the network's arc capacities are subject to random variation. This paper provides this methodology by describing a Monte Carlo sampling plan that allows one to conduct a sensitivity analysis for a variable upper bound on the flow capacity of a specified arc. The proposed plan has two notable features. It permits estimation of the probabilities of a feasible flow for many values of the upper bound on the arc capacity from a single data set generated by the Monte Carlo method at a single value of this upper bound. Also, the resulting estimators have considerably smaller variancesthan crude Monte Carlo sampling would produce in the same setting. The success of the technique follows from the use of lower and upper bounds on each probability of interest where the bounds are generated from an established method of decomposing the capacity state space.

GIaz and Johnson [14] introduce ith-order product-type approximations, βi, i =1,…n − 1, for Pn = P(X1 ≤c1, X2 ≤ c2,…Xn≤ cn) and show that Pn≥ βn−1 ≥ βn−2 ≥… ≥ β2 ≥ β1 when X is MTP2. In this article, it is shown that

under weaker positive dependence conditions. For multivariate normal distributions, these conditions reduce to cov(Xi,Xj) ≥ 0 for 1 ≤ i < j ≤ n and cov(Xi,Xj| Xj−1) ≥ 0 for 1 ≤ i < j − 1, j = 3,…,n. This is applied to group sequential analysis with bivariate normal responses. Conditions for Pn ≥ β3 ≥ β2 ≥β1 are also derived. Bound conditions are also obtained that ensure that product-type approximations are nested lower bounds to upper orthant probabilities P(X1 > C1,…,Xn > cn). It is shown that these conditions are satisfied for the multivariate exponential distribution of Marshall and Olkin [20].

We analyze gated, exhaustive service of an infinite-server system with vacations. Customers enter a queue in a Poisson stream. The servers, working in parallel, serve customers in stages. A stage begins with all customers transferred from the queue to the servers (the gate opens). The servers then begin serving these customers, all simultaneously. The stage ends when their services are completed. Service is exhaustive because the servers must again examine the queue to see if any new customers arrived during the last stage. If there are any, a new stage begins. If there are none, the servers move on to other work. The time spent away from the queue is called vacation time. The queue may represent a node or station in a data transmission network and the servers may be communication channels.

We analyze the equilibrium behavior of the number of requests served during a stage for general service and vacation time distributions. This analysis leads to the solution of a Fredholm integral equation of the second kind. We find conditions under which the system is stable and compute bounds on performance metrics of interest. Approximate techniques are introduced and tested. Finally, an extension to polling systems is studied.

Consider m machines in series with unlimited intermediate buffers and n jobs available at time zero. The processing times of job j on all m machines are equal to a random variable Xj with distribution Fj. Various cost functions are analyzed using stochastic order relationships. First, we focus on minimizing where cj is the weight (holding cost) and Tj the completion time of job j. We establish that if are in a class of distributions we define as SIFR, and and are increasing sequences of likelihood ratio-ordered and stochastic-ordered random variables, respectively, the job sequence [1, 2, … n ] is optimal among all static permutation schedules. Second, for arbitrary processing time distributions, if is an increasing sequence of likelihood ratio-ordered (hazard rate-ordered) random variables and the costs are nonincreasing, then a general cost function is minimized by the job sequence [1,2,…, n] in the stochastic ordering (increasing convex ordering) sense.

Four practically important extensions of the classical age-replacement problem are analyzed using Markov decision theory: (1) opportunity maintenance, (2) imperfect repair, (3) non-zero repair times, and (4) Markov degradation of the working unit. For this general model, we show that the optimal maintenance policy is of the control limit type and that the average costs are a unimodal function of the control limit. An efficient optimization procedure is provided to find the optimal policy and its average costs. The analysis extends and unifies existing results.

The mechanism of the Counter Scheme (CS) has been shown to be an effective statistical approach for the reorganization of linear lists, where the records in the list are referenced independently with a time homogeneous multinomial distribution. In this paper we show that derivative schemes can be used effectively in other contexts as well. Specifically, we consider (a) linear lists that are doubly linked, so that they may be accessed at both ends, (b) multilists, which result from dissecting a linear list into several pieces that are accessed independently and reside in WORM (write-once-read-many) store, and (c) reorganizing a disk, by copying its contents to another disk, so as to minimize the expected seek time required to access a record.

Two approaches for simulating the reliability function are considered–one using the total hazard estimator and the other using importance sampling. It is shown both for the Wheatstone Bridge System and for a triangular system that the total hazard estimator has significantly smaller variance when compared both to the standard importance sampling estimator and to an improved version of it.

In this paper we give a short proof of a general version of Theorem 3.3 of Benkherouf [2].

Some monotonicity properties and bounds on expectations of certain functions of minimal repair times and interminimal repair times are obtained under assumptions on the aging characteristics of the equipment under maintenance.

This paper proposes a method that allows the construction of discrete-state Markov chains approximating an Ito-diffusion process. The transition probabilities of the Markov chains are chosen in such a way that functionals converge with a desired weak order with respect to vanishing step size under sufficient smoothness assumptions.

Markov modulated fluid models are studied in this paper. When the input of the fluid model is represented by one Markov chain, two approaches are given that result in asymptotic expressions for the overflow probability. Both approaches are based on large deviations theories. The equivalence of the expressions is proved. When the input is represented by N similar Markov chains, a reduction property is derived.

An external uniformization technique was developed by Ross [4] to obtain approximations of transition probabilities of finite Markov chains in continuous time. Yoon and Shanthikumar [7] then reported through extensive numerical experiments that this technique performs quite well compared to other existing methods. In this paper, we show that external uniformization results from the strong law of large numbers whose underlying distributions are exponential. Based on this observation, some remarks regarding properties of the approximation are given.

In this paper we present two examples of physically realizable processes whose spectral density is not “physically realizable.”

This paper proposes a logistic approximation to the upper tail of the t distribution and its inverse that is more convenient and more accurate than those of Shah and Allen [3], and Koehler [1] and Lin [2], when measured in terms of the number of keystrokes and absolute relative errors, respectively.

This paper deals with the two-dimensional stochastic process (X(t), V(t)) where dX(t) = V(t)dt, V(t) = W(t) + ν for some constant ν and W(t) is a one-dimensional Wiener process with zero mean and variance parameter σ2= 1. We are interested in the first-passage time of (X(t), V(t)) to the plane X = 0 for a process starting from (X(0) = −x, V(0) = ν) with x > 0. The partial differential equation for the Laplace transform of the first-passage time density is transformed into a Schrödinger-type equation and, using methods of global analysis, such as the method of dominant balance, an approximation to the first-passage density is obtained. In a series of simulations, the quality of this approximation is checked. Over a wide range of x and ν it is found to perform well, globally in t. Some applications are mentioned.

Data analytic techniques are used in the construction of a simple approximation to the inverse normal tail probability function. The approximation is more accurate and more convenient than Hamaker's [2] over a wide range, when measured in terms of the number of keystrokes and absolute relative error.

Recently an error-bound theorem was reported to conclude analytic error bounds for approximate Markov chains. The theorem required a uniform bound for marginal expectations of the approximate model. This note will relax this bound to steady state rather than marginal expectations as of practical interest

(i) to simplify verification and/or

(ii) to obtain a more accurate error bound.

A communication model is studied in detail to support the results.

In 1987, Sheldon M. Ross [4] gave an interesting recurrent relation method for approximations of important functions in renewal theory. Using his idea and Feller's technique for inverting Laplace transforms, we obtain a general method for recurrent approximations to the solutions of renewal-type integral equations.

We present a fast algorithm for random numbers distributed uniformly on (0,1). In contrast to most other generators, it uses no floating point operations. Instead, the internal bit representation of the numbers is generated directly from a random bit source. It can easily be implemented in high-level languages like Modula-2 and shows good empirical behavior.