Two simple control policies for a multicomponent maintenance system

Control Systems;Maintenance;controle-systemen

Analysis and computation of (n,N): Strategies for maintenance of a two-component system

Computer Science;produktieleer/ produktieplanning

Optimizing flow rates in a queueing network with side constraints

Network Analysis;operations research

Coordinated replenishment systems with discount opportunities

Inventory Control;Inventory Models;inkoop

A note on exponential dispersion models which are invariant under length-biased sampling

Length-biased sampling situations may occur in clinical trials, reliability, queueing models, survival analysis and population studies where a proper sampling frame is absent.In such situations items are sampled at rate proportional to their length so that larger values of the quantity being measured are sampled with higher probabilities.More specifically, if f(x) is a p.d.f. presenting a parent population composed of nonnegative valued items then the sample is practically drawn from a distribution with p.d.f. g(x) = xf(x)/E(X) describing the lengthbiased population.In this case the distribution associated with g is termed a length-biased distribution.In this note we present a unified approach for characterizing exponential dispersion models which are invariant, up to translations, under various types of length-biased sampling.The approach is rather simple as it reduces such invariance problems into differential equations in terms of the derivatives of the associated variance functions.sampling;variance;models;distribution;statistics

Approximations for the delivery splitting model

Consumer Demand;Operational Research;Stocks

Group Testing Models with Processing Times and Incomplete Identification

We consider the group testing problem for a finite population of possibly defective items with the objective of sampling a prespecified demanded number of nondefective items at minimum cost.Group testing means that items can be pooled and tested together; if the group comes out clean, all items in it are nondefective, while a "contaminated" group is scrapped.Every test takes a random amount of time and a given deadline has to be met.If the prescribed number of nondefective items is not reached, the demand has to be satisfied at a higher (penalty) cost.We derive explicit formulas for the distributions underlying the cost functionals of this model.It is shown in numerical examples that these results can be used to determine the optimal group size.testing;sampling

Hypergeometric Group Testing with Incomplete Information

We study several group testing models with and without processing times.The objective is to choose an optimal group size for pooled screening of a contaminated population so as to collect a prespeciffied number of good items from it with minimumtesting expenditures.The tested groups that are found contaminated are used as new sampling population in later stages of the procedures.Since testing may be time-consuming, we also consider deadlines to be met for the testing process.We derive algorithms and exact results for the underlying distributions enabling us to find optimal procedures.Several numerical examples are given.testing;incomplete information