Coordinated scheduling of customer orders for quick response

The scheduling problem addressed in this paper concerns a manufacturer who produces a variety of product types and operates in a make‐to‐order environment. Each customer order consists of known quantities of the different product types, and must be delivered as a single shipment. Periodically the manufacturer schedules the accumulated and unscheduled customer orders. Instances of this problem occur across industries in manufacturing as well as in service environments. In this paper we show that the problem of minimizing the weighted sum of customer order delivery times is unary NP‐hard. We characterize the optimal schedule, solve several special cases of the problem, derive tight lower bounds, and propose several heuristic solutions. We report the results of a set of computational experiments to evaluate the lower bounding procedures and the heuristics, and to determine optimal solutions. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

A class of continuous nonlinear programming problems with time-delayed constraints

A general class of continuous time nonlinear problems is considered. Necessary and sufficient conditions for the existence of solutions are established and optimal solutions are characterized in terms of a duality theorem. The theory is illustrated by means of an example.     

Minimum cost sampling plans using bayesian methods

This article considers a general method for acceptance/rejection decisions in lot-by-lot sampling situations. Given arbitrary cost functions for sampling, accepting, and rejecting (where the cost can depend on the quality of the item) and a prior distribution on supplier quality, formulas are derived that lead to the minimal cost single-staged inspection plan. For the Bernoulli case, where each item is classified as acceptable or defective, the formulas simplify immensely. A computer code for solving the Bernoulli case is given.     

Estimating critical path and arc probabilities in stochastic activity networks

This article describes a new procedure for estimating parameters of a stochastic activity network of N arcs. The parameters include the probability that path m is the longest path, the probability that path m is the shortest path, the probability that arc i is on the longest path, and the probability that arc i is on the shortest path. The proposed procedure uses quasirandom points together with information on a cutset ? of the network to produce an upper bound of O[(log K)^N?|?|+1/K] on the absolute error of approximation, where K denotes the number of replications. This is a deterministic bound and is more favorable than the convergence rate of 1/K^1/2 that one obtains from the standard error for K independent replications using random sampling. It is also shown how series reduction can improve the convergence rate by reducing the exponent on log K. The technique is illustrated using a Monte Carlo sampling experiment for a network of 16 relevant arcs with a cutset of ? = 7 arcs. The illustration shows the superior performance of using quasirandom points with a cutset (plan A) and the even better performance of using quasirandom points with the cutset together with series reduction (plan B) with regard to mean square error. However, it also shows that computation time considerations favor plan A when K is small and plan B when K is large.     

Testing goodness of fit to the increasing failure rate family

One branch of the reliability literature is concerned with devising statistical procedures with various nonparametric “restricted family” model assumptions because of the potential improved operating characteristics of such procedures over totally nonparametric ones. In the single-sample problem with unknown increasing failure rate (IFR) distribution F, (1) maximum-likelihood estimators of F have been calculated, (2) upper or lower tolerance limits for F have been determined, and (3) tests of the null hypothesis that F is exponential have been constructed. Barlow and Campo proposed graphical methods for assessing goodness of fit to the IFR model when the validity of this assumption is unknown. This article proposes several analytic tests of the IFR null hypothesis based on the maximum distance and area between the cumulative hazard function and its greatest convex minorant (GCM), and the maximum distance and area between the total time on test statistic and its GCM. A table of critical points is provided to implement a specific test having good overall power properties.     

Testing goodness of fit to the increasing failure rate family with censored data

One important thrust in the reliability literature is the development of statistical procedures under various “restricted family” model assumptions such as the increasing failure rate (IFR) and decreasing failure rate (DFR) distributions. However, relatively little work has been done on the problem of testing fit to such families as a null hypothesis. Barlow and Campo proposed graphical methods for assessing goodness of fit to the IFR model in single-sample problems. For the same problem with complete data, Tenga and Santner studied several analytic tests of the null hypothesis that the common underlying distribution is IFR versus the alternative that it is not IFR for complete data. This article considers the same problem for the case of four types of censored data: (i) Type I (time) censoring, (ii) Type I1 (order statistic) censoring, (iii) a hybrid of Type I and Type I1 censoring, and (iv) random censorship. The least favorable distributions of several intuitive test statistics are derived for each of the four types of censoring so that valid small-sample-size α tests can be constructed from them. Properties of these tests are investigated.     

Causal Linkages Between Domestic Terrorism and Economic Growth

We use the Hsiao–Granger method to test for terrorism–growth causality for seven Western European countries. In bivariate settings, the impact of economic performance on domestic terrorism is very strong. In trivariate settings, the impact of performance on terrorism diminishes. In general, we find that economic performance leads terrorist violence in robust ways only for three out of seven countries. Terrorism is almost never found to causally influence growth in bivariate and trivariate specifications. Our findings indicate that the role of economic performance in determining terrorist violence appears to have been important for some countries, whereas all attacked economies have been successful in adjusting to the threat of terrorism.     

Book review

Steven L. Burg and Paul S. Shoup, The War in Bosnia‐Herzegovina: Ethnic Conflict and International Intervention.New York: M.E. Sharpe, 1999. Pp.xviii + 499, maps, tables, notes, biobliog., index. NP. ISBN 1–56324–308–3.