Developing an optimal repair-replacement strategy for pallets

A Markovian model is presented for the development of an optimal repair-replacement policy for the situation requiring a decision only at failure. The problem is characterized by the presence of growth which is integrated into the formulation. The model is applied to an actual problem, with data analysis and results given. Substantial savings are indicated.     

Expedients for solving some specially structured mixed-integer programs

In this paper we consider dual angular and angular structured mixed integer programs which arise in some practical applications. For these problems we describe efficient methods for generating a desirable set of Benders' cuts with which one may initialize the partitioning scheme of Benders. Our research is motivated by the computational experience of McDaniel and Devine who have shown that the set of Benders' cuts which are binding at the optimum to the linear relaxation of the mixed integer program, play an important role in determining an optimal mixed integer solution. As incidental results in our development, we provide some useful remarks regarding Benders' and Dantzig-Wolfe's decomposition procedures. The computational experience reported seems to support the expedients recommended in this paper.     

The cyclic separation scheduling problem

This paper deals with the problem of scheduling items (tasks, employees, equipment, etc.) over a finite time horizon so as to minimize total cost expenditures while maintaining a predefined separation between certain items. The problem is cyclic, because the same schedule will be repeated over several consecutive time periods of equal length. Thus, requirements are present to maintain the separation of items not only within the individual time periods considered, but also between items in adjoining periods. A special purpose branch-and-bound algorithm is developed to solve this scheduling problem by taking advantage of its cyclic nature. Computational results are given.     

Analysis and optimal design of discrete order picking technologies along a line

Order picking accounts for most of the operating expense of a typical distribution center, and thus is often considered the most critical function of a supply chain. In discrete order picking a single worker walks to pick all the items necessary to fulfill a single customer order. Discrete order picking is common not only because of its simplicity and reliability, but also because of its ability to pick orders quickly upon receipt, and thus is commonly used by e‐commerce operations. There are two primary ways to reduce the cost (walking distance required) of the order picking system. First is through the use of technology—conveyor systems and/or the ability to transmit order information to pickers via mobile units. Second is through the design—where best to locate depots (where workers receive pick lists and deposit completed orders) and how best to lay out the product. We build a stochastic model to compare three configurations of different technology requirements: single‐depot, dual‐depot, and no‐depot. For each configuration we explore the optimal design. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

A branch‐and‐price approach for the stochastic generalized assignment problem

In this article, we address a stochastic generalized assignment machine scheduling problem in which the processing times of jobs are assumed to be random variables. We develop a branch‐and‐price (B&P) approach for solving this problem wherein the pricing problem is separable with respect to each machine, and has the structure of a multidimensional knapsack problem. In addition, we explore two other extensions of this method—one that utilizes a dual‐stabilization technique and another that incorporates an advanced‐start procedure to obtain an initial feasible solution. We compare the performance of these methods with that of the branch‐and‐cut (B&C) method within CPLEX. Our results show that all B&P‐based approaches perform better than the B&C method, with the best performance obtained for the B&P procedure that includes both the extensions aforementioned. We also utilize a Monte Carlo method within the B&P scheme, which affords the use of a small subset of scenarios at a time to estimate the “true” optimal objective function value. Our experimental investigation reveals that this approach readily yields solutions lying within 5% of optimality, while providing more than a 10‐fold savings in CPU times in comparison with the best of the other proposed B&P procedures. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 131–143, 2014     

The Political Economy of Legislation on Terrorism

^{1 1}This research was funded in part by a grant from the Lowe Institute of Political Economy. The corresponding author is S. Brock Blomerg. We thank Chris Blomberg and Brianna Loyosa for their excellent research assistance on the project. This paper presents an empirical analysis of what drives congressional legislation on terrorism during the period 1995 to 2010. We utilize and augment current methodology to compile and analyze data on sponsorship and cosponsorship of terrorism related data. Our results on the sources of legislation on terrorism are largely in line with past examinations of the importance of committee membership and leadership, party majority-ship, and other political factors. Further, we find that the most significant and robust drive for legislation on terrorism is the September 11^th attacks. And while the impact of 9/11 affected legislative productivity everywhere, we find that it most significantly affected states surrounding New York and Washington D.C. Our results indicate that the economy may be one factor motivating politicians to legislate on terrorism; however, these results are not robust.     

The BWC protocol mandate for failure

The stage may be set for what could be a historic turning point in America's reliance on nuclear weapons to meet its fundamental national security interests. Proponents of a refurbished nuclear stockpile and infrastructure are convinced that nuclear weapons will remain central to U.S. security interests, yet they admit that there is no national consensus on the need for and role of nuclear weapons. Nuclear opponents are gravely concerned that to the extent nuclear refurbishment creates a global perception that nuclear weapons remain essential instruments, it will eviscerate nuclear nonproliferation measures precisely at a time when nuclear ambitions are growing. Moreover, opponents see deterrence through advanced conventional weapons as decisively more credible than any nuclear alternative. With hopes of elevating discourse to the national level, this article examines the key current arguments pro and con within the specialist community and forecasts changes in the U.S. nuclear arsenal over the next decade. It concludes with a brief prognosis on prospects for complete nuclear disarmament.