The collection depots location problem on networks

In this paper we investigate the collection depots location problem on a network. A facility needs to be located to serve a set of customers. Each service consists of a trip to the customer, collecting materials, dropping the materials at one of the available collection depots and returning to the facility to wait for the next call. Two objectives are considered: minimizing the weighted sum of distances and minimizing the maximum distance. The properties of the solutions to these problems are described. © 2002 John Wiley & Sons, Inc. Naval Research Logistics, 49: 15–24, 2002; DOI 10.1002/nav.10000     

Outbound supply chain network design with mode selection and lead time considerations

We present a large‐scale network design model for the outbound supply chain of an automotive company that considers transportation mode selection (road vs. rail) and explicitly models the relationship between lead times and the volume of flow through the nodes of the network. We formulate the problem as a nonlinear zero‐one integer program, reformulate it to obtain a linear integer model, and develop a Lagrangian heuristic for its solution that gives near‐optimal results in reasonable time. We also present scenario analyses that examine the behavior of the supply chain under different parameter settings and the performance of the solution procedures under different experimental conditions. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Homophobic legislation and its impact on human security

Despite sustained opposition, legislation criminalising homosexuality persists and threatens human security in Africa in numerous ways. This paper explores the circumstances around the enactment of new anti-homosexual legislation in Nigeria and Uganda, examining five categories of insecurity faced by lesbian, gay, bisexual, and transgender (LGBT) people in the context of these laws: physical violence; extortion and blackmail; arbitrary arrest and detention; displacement from home; and loss of work.     

Bayesian estimation: A sensitivity analysis

The robustness of the assigned prior distribution in a Bayesian estimation problem is examined. A Bayesian analysis for a stochastic intensity parameter of a Poisson distribution is summarized in which the natural conjugate is assigned as the prior distribution of the random parameter. The sensitivity analysis is carried out by assuming the existence of a true prior which is different in form from that of the assigned prior distribution. By using mean-squared error as a measure of performance, the ensuing Bayes decision function is compared to the corresponding minimum variance unbiased estimator. Results indicate that the Bayes estimator is largely robust to deviations from the assigned prior and remains squared-error superior to the MVU type within a broad region.     

The gradual covering problem

In this paper we investigate the gradual covering problem. Within a certain distance from the facility the demand point is fully covered, and beyond another specified distance the demand point is not covered. Between these two given distances the coverage is linear in the distance from the facility. This formulation can be converted to the Weber problem by imposing a special structure on its cost function. The cost is zero (negligible) up to a certain minimum distance, and it is a constant beyond a certain maximum distance. Between these two extreme distances the cost is linear in the distance. The problem is analyzed and a branch and bound procedure is proposed for its solution. Computational results are presented. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Balancing and optimizing a portfolio of R&D projects

A mathematical formulation of an optimization model designed to select projects for inclusion in an R&D portfolio, subject to a wide variety of constraints (e.g., capital, headcount, strategic intent, etc.), is presented. The model is similar to others that have previously appeared in the literature and is in the form of a mixed integer programming (MIP) problem known as the multidimensional knapsack problem. Exact solution of such problems is generally difficult, but can be accomplished in reasonable time using specialized algorithms. The main contribution of this paper is an examination of two important issues related to formulation of project selection models such as the one presented here. If partial funding and implementation of projects is allowed, the resulting formulation is a linear programming (LP) problem which can be solved quite easily. Several plausible assumptions about how partial funding impacts project value are presented. In general, our examples suggest that the problem might best be formulated as a nonlinear programming (NLP) problem, but that there is a need for further research to determine an appropriate expression for the value of a partially funded project. In light of that gap in the current body of knowledge and for practical reasons, the LP relaxation of this model is preferred. The LP relaxation can be implemented in a spreadsheet (even for relatively large problems) and gives reasonable results when applied to a test problem based on GM's R&D project selection process. There has been much discussion in the literature on the topic of assigning a quantitative measure of value to each project. Although many alternatives are suggested, no one way is universally accepted as the preferred way. There does seem to be general agreement that all of the proposed methods are subject to considerable uncertainty. A systematic way to examine the sensitivity of project selection decisions to variations in the measure of value is developed. It is shown that the solution for the illustrative problem is reasonably robust to rather large variations in the measure of value. We cannot, however, conclude that this would be the case in general. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 18–40, 2001     

Open shop scheduling to minimize the number of late jobs

We develop polynomial algorithms for several cases of the NP-hard open shop scheduling problem of minimizing the number of late jobs by utilizing some recent results for the open shop makespan problem. For the two machine common due date problem, we assume that either the machines or the jobs are ordered. For the m machine common due date problem, we assume that one machine is maximal and impose a restriction on its load. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 525–532, 1998     

Power approximations in the economic design of control charts

A new approximate method is proposed for the economic design of control charts based on an estimate of the power of the control chart at optimality. Multiple linear regression is employed for the derivation of the approximate formula expressing the power of the control chart as a function of the model parameters. A simple optimization procedure is then used to determine the economic design of the control chart for the predicted value of the chart's detection power. The application of the new approach is illustrated through Duncan's models for variables control charts for processes subject to single and multiple assignable causes. Evaluation of the performance of the approximate method indicates that the approximate control chart design is very close to the exact optimum while its implementation requirements are reduced.     

Monte Carlo estimation of the maximal flow distribution with discrete stochastic arc capacity levels

This article describes a highly efficient Monte Carolo sampling plan for estimating ordinates of the complementary distribution function of the maximal s-t flow in a directed network with source node s, terminal node t and whose arcs assume random capacities. Communication, electric power, transportation, and water distribution systems fit this representation. The article derives point estimates and interval estimates that hold for finite sample sizes, and shows the extent to which the proposed technique saves time, as compared to crude Monte Carlo sampling, in achieving a specified accuracy.     

Level crossing analysis of priority queues and a conservation identity for vacation models

The two purposes of this article are to illustrate the power and simplicity of level crossing analysis and to present a conservation identity for M/G/1 priority queues with server vacations. To illustrate the use of level crossing analysis we apply it to preemptive (resume) priority M/G/1 queues with single- and multiple-server vacations considered by Kella and Yechiali (1986) and to non-preemptive priority M/M/c queues considered by Kella and Yechiali (1985). The conservation identity presented here states that the ratios of mean waiting times in an M/G/1 queue with and without server vacation policies are independent of the service discipline for first come first served, shortest processing time, shortest processing time within generations and non-preemptive priority service disciplines.