In this article we will derive some results for characterizing the almost closed sets of a face-homogeneous random walk. We will present a conjecture on the relation between discrete scattering of the fluid limit and the absence of nonatomic almost closed sets. We will illustrate the conjecture with random walks with both simple and nonsimple decomposition into almost closed sets.

Consider a tandem queuing network with an infinite supply of jobs in front of the first station, infinite room for completed jobs after the last station, finite buffers between stations, and a number of flexible servers who are subject to failures. We study the dynamic assignment of servers to stations with the goal of maximizing the long-run average throughput. Our main conclusion is that the presence of server failures does not have a major impact on the optimal assignment of servers to stations for the systems we consider. More specifically, we show that when the servers are generalists, any nonidling policy is optimal, irrespective of the reliability of the servers. We also provide theoretical and numerical results for Markovian systems with two stations and two or three servers that suggest that the structure of the optimal server assignment policy does not depend on the reliability of the servers and that ignoring server failures when assigning servers to stations yields near-optimal throughput. Finally, we present numerical results that illustrate that simple server assignment heuristics designed for larger systems with reliable servers also yield good throughput performance in Markovian systems with three stations and three failure-prone servers.

In this article we consider an insurance company selling life insurance policies. New policies are sold at random points in time, and each policy stays active for an exponential amount of time with rate μ, during which the policyholder pays premiums continuously at rate r. When the policy expires, the insurance company pays a claim of random size. The aim is to compute the probability of eventual ruin starting with a given number of policies and a given level of insurance fund. We establish the remarkable result that the ruin probability is identical to the one in the standard compound Poisson model where the insurance fund increases at constant rate r and claims occur according to a Poisson process with rate μ.

We consider the classical coupon collector's problem in which each new coupon collected is type i with probability pi; ∑i=1npi=1. We derive some formulas concerning N, the number of coupons needed to have a complete set of at least one of each type, that are computationally useful when n is not too large. We also present efficient simulation procedures for determining P(N > k), as well as analytic bounds for this probability.

We consider two multiclass discriminatory process sharing (DPS)-like time-shared M/G/1 queuing systems in which the weight assigned to a customer is a function of its class as well as (1) the attained service of the customer in the first system and (2) the residual processing time of the customer in the second system. We study the asymptotic slowdown, the ratio of expected sojourn time to the service requirement, of customers with very large service requirements. We also provide various results dealing with ordering of conditional mean sojourn times of any two given classes. We also show that the sojourn time of an arbitrary customer of a particular class in the standard DPS system (static weights) with heavy-tailed service requirements has a tail behavior similar to that of a customer from the same class that starts a busy period.

The Normal and Gamma distributions are the most popular models for analyzing symmetric and skewed data, respectively. In this article, a new multimodal distribution is introduced that contains the Normal and Gamma distributions as particular cases and thus could be a better model for both symmetric and skewed data. Various structural properties of this distribution are derived, including its moment-generating function, characteristic function, moments, entropy, asymptotic distribution of the extreme order statistics, method of moment estimates, maximum likelihood estimates, Fisher information matrix, and simulation issues. The superiority of the new distribution is illustrated by means of two real datasets.

In many companies, legacy systems have been used to serve customers arriving at service counters. The demand of a customer arriving at a counter is divided into R subdemands (SDs). Each SD is processed sequentially by the legacy system. When the final SD service is completed, the customer leaves the counter. On the other hand, Internet users desire that each SD be processed through the Internet without going to a service counter. We note that the applications for operating the web system differ from those of the legacy systems. For that reason, companies might use legacy systems for customers who come to the company through the Internet, without changing those legacy systems' applications. This web system, which is integrated with the legacy system, is called a front-end web system. Suppose that, for the web system, demands are generated according to a Poisson process. Then we show that the loss probability and macrostate distribution for the front-end web system are insensitive with respect to the distribution of the discrete random variable R, aside from the continuous distributions of other uncertain factors, under a restriction.

This article investigates TP2 dependence of sample spacings. It is proved that TP2 (RR2) dependence between a general spacing and a nonadjacent order statistic might be characterized by the DLR (ILR) property of the parent distribution, and TP2 dependence between any pair of consecutive spacings might be characterized by the DLR aging property of the population. Furthermore, TP2 dependence between any two consecutive spacings in multiple outliers exponential models is also derived. In addition, some applications in reliability and business auction are presented as well.