Scheduling on a single machine with a single breakdown to minimize stochastically the number of tardy jobs

Jobs with known processing times and due dates have to be processed on a machine which is subject to a single breakdown. The moment of breakdown and the repair time are independent random variables. Two cases are distinguished with reference to the processing time preempted by the breakdown (no other preemptions are allowed): (i) resumption without time losses and (ii) restart from the beginning. Under certain compatible conditions, we find the policies which minimize stochastically the number of tardy jobs.     

A proof for the longest-job-first policy in one-machine scheduling

We consider a one-machine scheduling problem with earliness and tardiness penalties. All jobs are assigned a common due date and the objective is to minimize the total penalty due to job earliness and tardiness. We are interested in finding the optimal combination of the common due-date value and the job sequence. Despite the fact that this problem in general is very hard to solve, we prove that there exists at least a common property for all optimal solutions: The first job in an optimal sequence is one of the longest jobs. We also prove that this property holds for a general class of unimodal penalty functions.     

Discount pricing policies for inventories subject to declining demand

Until only recently, the mechanism behind determining item price has been ignored and the discount price taken as a given in quantity-discount inventory decision problems. Inventory subject to declining demand further complicates both pricing and replenishment decisions. This article provides the vendor with the means for optimally determining both the discount price and replenishment order frequency for all buyers in the system in an environment of declining demand. In the multiple-buyer case, we provide an efficient algorithm for classifying buyers into homogeneous subgroups to further enhance joint cost savings among all system participants.     

Military Spending,Conflict and External Debt in Sub-Saharan Africa

The damaging economic effects of the debt crises on Africa in the late 1980s encouraged considerable research on the determinants of external debt in developing economies. Although sub-Saharan Africa's (SSA) debt was cut by two-thirds by 2008, through two debt relief programmes, debt in the region has since been rising at an increasingly rapid pace. This study provides an empirical analysis of the determinants of external debt in SSA over the period 1960–2016, using dynamic panel methods. It also considers two potentially important factors that have received relatively little attention. One is military spending, rarely considered, despite a number of well-publicised scandals over the procurement of unnecessary and expensive high-tech weapons systems. A second, is the possibility that the countries studied have been involved in conflict. The empirical results point to a positive impact of military spending on external debt, but with some evidence of heterogeneity across the countries. Furthermore, findings indicate that the positive effect of military expenditure on debt becomes more marked in countries that have been affected by conflict. These results imply that policies to improve security and reduce military spending could be beneficial in reducing external debt and, potentially, improving economic performance in the region.     

Single‐machine scheduling with deadlines to minimize the total weighted late work

We consider scheduling a set of jobs with deadlines to minimize the total weighted late work on a single machine, where the late work of a job is the amount of processing of the job that is scheduled after its due date and before its deadline. This is the first study on scheduling with the late work criterion under the deadline restriction. In this paper, we show that (i) the problem is unary NP‐hard even if all the jobs have a unit weight, (ii) the problem is binary NP‐hard and admits a pseudo‐polynomial‐time algorithm and a fully polynomial‐time approximation scheme if all the jobs have a common due date, and (iii) some special cases of the problem are polynomially solvable.     

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.     

Analysis of an Alternative Military Healthcare Benefit Design

Abstract

The Military Compensation and Retirement Modernization Commission was established by the Congress in 2013 to perform a systematic review of military compensation to address rising costs and other trends. Their recommendation for reforming the TRICARE health care program was sweeping, and differed greatly from earlier proposals that focused on increasing beneficiary cost shares. Specifically, the commission proposed overhauling the current benefit delivery model and replacing it with a premium-based insurance model offering a menu of DoD-sponsored private health plans. The analysis presented here is based on work that supported the commission by estimating the budgetary impact of its proposed reforms. Results indicate that movement towards the premium-based model would produce an annual budgetary cost savings in the $2 billion to $4 billion range, with a best savings estimate of $3.2 billion.