New inequalities for finite and infinite group problems from approximate lifting

In this paper, we derive new families of facet‐defining inequalities for the finite group problem and extreme inequalities for the infinite group problem using approximate lifting. The new valid inequalities for the finite group problem include two‐ and three‐slope facet‐defining inequalities as well as the first family of four‐slope facet‐defining inequalities. The new valid inequalities for the infinite group problem include families of two‐ and three‐slope extreme inequalities. These new inequalities not only illustrate the diversity of strong inequalities for the finite and infinite group problems, but also provide a large variety of new cutting planes for solving integer and mixed‐integer programming problems. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Optimum step‐stress accelerated life test plans for log‐location‐scale distributions

This article presents new tools and methods for finding optimum step‐stress accelerated life test plans. First, we present an approach to calculate the large‐sample approximate variance of the maximum likelihood estimator of a quantile of the failure time distribution at use conditions from a step‐stress accelerated life test. The approach allows for multistep stress changes and censoring for general log‐location‐scale distributions based on a cumulative exposure model. As an application of this approach, the optimum variance is studied as a function of shape parameter for both Weibull and lognormal distributions. Graphical comparisons among test plans using step‐up, step‐down, and constant‐stress patterns are also presented. The results show that depending on the values of the model parameters and quantile of interest, each of the three test plans can be preferable in terms of optimum variance. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

A multi-item EOQ model with inventory cycle balancing

This article concerns a multi-item, infinite-horizon, lot-sizing problem, where the objective is to minimize a total cost function made up of reordering cost, holding cost, and a cost determined by peak inventory levels. By spreading inventory replenishments over the reordering cycle, the peak inventory level can be reduced. The model permits the derivation of simultaneously optimal solutions for the length of the cycle and the individual item replenishment times within the cycle. An alternative formulation, in which total storage capacity is modeled as a constraint, is also solved.     

A discounted machine-replacement model with an expected future technological breakthrough

A machine-replacement problem is analyzed in a technological-development environment, in which a new-type machine (built by a new technology) may appear in the future. The solution of the replacement problem depends on purchasing, operating, and resale costs, and on the probability distribution of the market debut of the new technology, and it indicates whether to replace the existing machine now with an available similar type of machine, or to continue to operate the existing machine for at least one more period. A dynamic discounted cost model is presented, and a method is suggested for finding the optimal age for replacement of an existing machine (under rather general conditions of a technological environment). A solution procedure and a numerical example are given.     

Estimation from binomial data with classifiers of known and unknown imperfections

Observations from inspection by a “test” method and a standard method are combined to provide estimators of population proportion, and of probabilities of misclassification for the test method. Results of Hochberg and Tenenbein [3] and of Albers and Veldman [1] are extended to the case where the standard method is not perfect, but its misclassification probabilities have known values. Both moment and maximum-likelihood estimators are considered and some asymptotic properties of the resulting estimators are compared.     

Approximating nonstationary two-priority non-preemptive queueing systems

An approximation for analyzing transient and nonstationary two-priority non-preemptive queueing systems is presented. This system has a three-dimensional state space, and through use of state-space partitioning in conjunction with use of conditional surrogate distributions with constant parameters an approximation is designed. Regardless of system capacity K, the approximation requires the numerical solution of only ten differential equations, compared to the K² + K+1 Kolmogorov-forward equations required for the classic solution. Time-dependent approximations of the mean number of entities of type i and of the probability of a type-i entity being in service are obtained. Empirical test results over a wide range of systems indicate the approximation is quite accurate.     

A decision support system for the procurement of military equipment

The use of life-cycle costs in procurement is limited by the accuracy of cost estimates and assessments of availability risks under the conditions generating costs. Critical to these problems are the needs and responses of equipment to maintenance and repair. Using transition probabilities to define the relationships between serviceability and maintenance and repairs, this article develops a comprehensive decision support system for military procurement. It uses a dynamic programming model to determine the least-cost set of maintenance and repair decisions, where adjustments are included for warranty conditions, time value of money, the opportunity costs of equipment failure, and the end-of-cycle salvage values or disposal costs. The system allows users to define working and failed states, create their own rules or indicators of availability from estimates of state probabilities and establish thresholds of risk acceptability.     

An (s,S) inventory system with rest periods to the server

We study the (s,S) inventory system in which the server takes a rest when the level of the inventory is zero. The demands are assumed to occur for one unit at a time. The interoccurrence times between successive demands, the lead times, and the rest times are assumed to follow general distributions which are mutually independent. Using renewal and convolution techniques we obtain the state transition probabilities.