General models for the supplier's all-unit quantity discount policy

The purpose of this article is to investigate some managerial insights related to using the all-unit quantity discount policies under various conditions. The models developed here are general treatments that deal with four major issues: (a) one buyer or multiple buyers, (b) constant or price-elastic demand, (c) the relationship between the supplier's production schedule or ordering policy and the buyers' ordering sizes, and (d) the supplier either purchasing or manufacturing the item. The models are developed with two objectives: the supplier's profit improvement or the supplier's increased profit share analysis. Algorithms are developed to find optimal decision policies. Our analysis provides the supplier with both the optimal all-unit quantity discount policy and the optimal production (or ordering) strategy. Numerical examples are provided. © 1993 John Wiley & Sons. Inc.     

A Cryptographic Escrow for Treaty Declarations and Step-by-Step Verification

The verification of arms-control and disarmament agreements requires states to provide declarations, including information on sensitive military sites and assets. There are important cases, however, in which negotiations of these agreements are impeded because states are reluctant to provide any such data, because of concerns about prematurely handing over militarily significant information. To address this challenge, we present a cryptographic escrow that allows a state to make a complete declaration of sites and assets at the outset and commit to its content, but only reveal the sensitive information therein sequentially. Combined with an inspection regime, our escrow allows for step-by-step verification of the correctness and completeness of the initial declaration so that the information release and inspections keep pace with parallel diplomatic and political processes. We apply this approach to the possible denuclearization of North Korea. Such approach can be applied, however, to any agreement requiring the sharing of sensitive information.     

Server scheduling on parallel dedicated machines with fixed job sequences

We consider server scheduling on parallel dedicated machines to minimize the makespan. Each job has a loading operation and a processing operation. The loading operation requires a server that serves all the jobs. Each machine has a given set of jobs to process, and the processing sequence is known and fixed. We design a polynomial‐time algorithm to solve the two‐machine case of the problem. When the number of machines is arbitrary, the problem becomes strongly NP‐hard even if all the jobs have the same processing length or all the loading operations require a unit time. We design two heuristic algorithms to treat the case where all the loading times are unit and analyze their performance.     

Concise RLT forms of binary programs: A computational study of the quadratic knapsack problem

The reformulation‐linearization technique (RLT) is a methodology for constructing tight linear programming relaxations of mixed discrete problems. A key construct is the multiplication of “product factors” of the discrete variables with problem constraints to form polynomial restrictions, which are subsequently linearized. For special problem forms, the structure of these linearized constraints tends to suggest that certain classes may be more beneficial than others. We examine the usefulness of subsets of constraints for a family of 0–1 quadratic multidimensional knapsack programs and perform extensive computational tests on a classical special case known as the 0–1 quadratic knapsack problem. We consider RLT forms both with and without these inequalities, and their comparisons with linearizations derived from published methods. Interestingly, the computational results depend in part upon the commercial software used. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Dominating sets for rectilinear center location problems with polyhedral barriers

In planar location problems with barriers one considers regions which are forbidden for the siting of new facilities as well as for trespassing. These problems are important since they model various actual applications. The resulting mathematical models have a nonconvex objective function and are therefore difficult to tackle using standard methods of location theory even in the case of simple barrier shapes and distance functions. For the case of center objectives with barrier distances obtained from the rectilinear or Manhattan metric, it is shown that the problem can be solved in polynomial time by identifying a dominating set. The resulting genuinely polynomial algorithm can be combined with bound computations which are derived from solving closely connected restricted location and network location problems. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 647–665, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10038     

Scheduling jobs with piecewise linear decreasing processing times

We study the problems of scheduling a set of nonpreemptive jobs on a single or multiple machines without idle times where the processing time of a job is a piecewise linear nonincreasing function of its start time. The objectives are the minimization of makespan and minimization of total job completion time. The single machine problems are proved to be NP‐hard, and some properties of their optimal solutions are established. A pseudopolynomial time algorithm is constructed for makespan minimization. Several heuristics are derived for both total completion time and makespan minimization. Computational experiments are conducted to evaluate their efficiency. NP‐hardness proofs and polynomial time algorithms are presented for some special cases of the parallel machine problems. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 531–554, 2003     

An error components model of cost overruns and schedule slip on army R&D programs

What has been causing cost overruns and schedule slippages in Army major weapon-system R&D programs during the past ten years? This article addresses this question with emphasis on the effectiveness of an Army acquisition strategy entitled Total Risk Assessing Cost Estimating (TRACE). An empirical study employed a questionnaire and interviews with key personnel from all of the major Army Program Management Offices involved with R&D. The major research question was the following: What explanatory variables have been affecting R&D cost overruns and development time? This includes an evaluation of TRACE as a potential explanatory variable. Data was collected and analyzed using an error components multiple regression model. The major explanatory variables that appeared to explain cost overruns were technological risk of the program, education and experience of key program management office personnel, and the degree of “buy in” by the prime contractor. Strong statistical results indicate that TRACE is having little or no effect on cost overruns. In the case of development time, the major explanatory variables were seen to be technological risk of the program, testing, TRACE, education, and length of the R&D contract.     

A simulation study of the efficiency of empirical Bayes' estimators of multiple correlated probability vectors

Empirical Bayes' methods had been used by Brier, Zacks, and Marlow [1] for estimating performance characteristic vectors of success probabilities. The problem is that of estimating k-dimensional success probabilities of dependent binomial random variables, which are highly correlated. The present study reinforces the results of the previous one by showing, via simulations, that the relative efficiency of the empirical Bayes estimators, compared to the Stein-type and to the maximum-likelihood ones, is very high. This holds even if the success proportions are based on a small number of trials. We study the case of equicorrelation structure with positive correlations.     

Health Insurance,Health Conditions,and Veteran Health Care Utilization

Abstract

The utilization of health care services by veterans has received much attention in recent years. However, the impact of the large array of factors affecting the veterans’ demand for health care services remains understudied. These factors include individual socio-demographic and economic characteristics, the availability of various sources of health insurance, and the prevalence of medical conditions. We use public data to analyze how veterans’ utilization of health care services varies with these factors. We also analyze how the reliance on VA services varies when alternative sources of health insurance are available to veterans. Based on the estimated relationships, we use a micro-simulation model to forecast future health care utilization, both inside and outside of VA.     

Average-case analysis of the bin-packing problem with general cost structures

We consider a version of the famous bin-packing problem where the cost of a bin is a concave function of the number of items in the bin. We analyze the problem from an average-case point of view and develop techniques to determine the asymptotic optimal solution value for a variety of functions. We also describe heuristic techniques that are asymptotically optimal. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 673–686, 1997