Waiting times for M/G/1 queues with service-time or delay-dependent server vacations

This article shows how to determine the stationary distribution of the virtual wait in M/G/1 queues with either one-at-a-time or exhaustive server vacations, depending on either service times or accrued workload. For the first type of dependence, each vacation time is a function of the immediately preceding service time or of whether the server finds the system empty after returning from vacation. In this way, it is possible to model situations such as long service times followed by short vacations, and vice versa. For the second type of dependence, the vacation time assigned to an arrival to follow its service is a function of the level of virtual wait reached. By this device, we can model situations in which vacations may be shortened whenever virtual delays have gotten excessive. The method of analysis employs level-crossing theory, and examples are given for various cases of service and vacation-time distributions. A closing discussion relates the new model class to standard M/G/1 queues where the service time is a sum of variables having complex dependencies. © 1992 John Wiley & Sons, Inc.     

The reporting time problem: Integration of intelligence with verification

This article is a theoretic study of the following problem in verification: Mobile units under control of an agent, whom we call the HIDER, travel on a known transportation network and must at the conclusion of their itinerary report locations at fixed time intervals to a monitoring authority, whom we call the SEEKER. The purpose of this reporting requirement is to verify that illegal units do not infiltrate the network from sources under the control of the HIDER. We assume that the SEEKER has an independent intelligence-gathering capability which gives sightings of both legal and illegal units. The purpose of this article is to quantify the advantage of frequent over infrequent reporting. © 1992 John Wiley & Sons, Inc.     

Book reviews

Winning the Next War: Innovation and the Modern Military. By Stephen Peter Rosen. Cornell Studies in Security Affairs, Cornell University Press, New York (1991), ISBN 0-8014-2566-5. Price £40.00

Post-Military Society. By Martin Shaw. Polity Press, Cambridge (1991), ISBN 0-7456-01987 (hardback) £35.00,0-7456-01995 (paperback) £11.95

Big Boys' Rules—The Secret War Against the IRA. By Mark Urban. Faber and Faber, London (1992), ISBN 0-571-16112-X, £14.99     

On testing for decreasing mean residual life ordering

We consider the problem of testing for the decreasing mean residual life ordering introduced in Kochar and Wiens [14]. We treat both the one-sample and two-sample problems. The limiting distributions of the proposed test statistics are derived. © 1993 John Wiley & Sons, Inc.     

Local search techniques for the generalized resource constrained project scheduling problem

In this article we address the problem of scheduling a single project network with both precedence and resource constraints through the use of a local search technique. We choose a solution definition which guarantees precedence feasibility, allowing the procedure to focus on overcoming resource infeasibility. We use the 110-problem data set of Patterson to test our procedure. Our results indicate a significant improvement over the best heuristic results reported to date for these problems (Bell and Han [1]). Two major advantages of the local search algorithm are its ability to handle arbitrary objective functions and constraints and its effectiveness over a wide range of problem sizes. We present a problem example with an objective function and resource constraints which include nonlinear and non-continuous components, which are easily considered by the procedure. The results of our algorithm are significantly better than random solutions to the problem. © 1993 John Wiley & Sons, Inc.     

Composite unimodality

This article defines a class of univariate functions termed composite unimodal, and shows how their minimization admits an effective search procedure, albeit one not as efficient as is Fibonacci search for unimodal functions. An approximate Lagrangian approach to an important real-world logistics problem is seen to yield a surrogate problem whose objective function is composite unimodal. The mathematical form of this objective function is likely to be encountered in solving future real-world problems. © 1993 John Wiley & Sons, Inc.     

Optimal base stock policies and truck capacity in a two-echelon system

With the recent trend toward just-in-time deliveries and reduction of inventories, many firms are reexamining their inventory and logistics policies. Some firms have dramatically altered their inventory, production, and shipping policies with the goal of reducing costs and improving service. Part of this restructuring may involve a specific contract with a trucking company, or it may entail establishing in-house shipping capabilities. This restructuring, however, raises new questions regarding the choice of optimal trucking capacity, shipping frequency, and inventory levels. In this study, we examine a two-level distribution system composed of a warehouse and a retailer. We assume that demand at the retailer is random. Since the warehouse has no advance notice of the size of the retailer order, inventory must be held there as well as at the retailer. We examine inventory policies at both the warehouse and the retailer, and we explicitly consider the trucking capacity, and the frequency of deliveries from the warehouse to the retailer. Both linear and concave fixed transportation costs are examined. We find the optimal base stock policies at both locations, the optimal in-house or contracted regular truck capacity, and the optimal review period (or, equivalently, delivery frequency). For the case of normally distributed demand we provide analytical results and numerical examples that yield insight into systems of this type. Some of our results are counterintuitive. For instance, we find some cases in which the optimal truck capacity decreases as the variability of demand increases. In other cases the truck capacity increases with variability of demand. © 1993 John Wiley & Sons, Inc.