Component part stocking policies

This article presents research designed to aid firms who assemble many components into a final product. We assume that purchase quantities are fixed, and that all parts and components are assembled at one stage in a short time. Demand for the final product is represented by a stationary independent and identically distributed random variable; and unmet demand is backordered. Ordering is done on a periodic review basis. We develop infinite horizon, approximate expected cost, and expected service level functions, and we present an algorithm for finding approximately minimum cost reorder points for each part subject to a service level constraint. Extensive results on the accuracy of the approximations are presented. Due to the size of the problem, we present only limited results on the performance of the optimization algorithm.     

See the light: Optimization of put-to-light order picking systems

Put-to-light order picking systems invert the basic logic of conventional picker-to-parts systems. Instead of successively visiting the storage positions of the stock keeping units (SKUs) when collecting picking orders, an order picker accompanies successive bins each containing multiple items of a specific SKU along a lane of subsequent orders. Whenever the picker passes an order requiring the current SKU, which is indicated by a light signal, she puts the requested number of items into the bin associated with the order. Such an order picking system is well-suited if the assortment is not overly large and all orders demand similar SKUs, so that it is mainly applied in distribution centers of brick-and-mortar retail chains. This paper evaluates four different setups of put-to-light systems, which, during operations, require the solution of different storage assignment and SKU sequencing problems. We formulate these problems, prove computational complexity, and suggest suited solution algorithms. By applying these algorithms in a comprehensive computational study, we benchmark the impact of the four different setups on picking performance. In this way, warehouse managers receive decision support on how to set up their put-to-light systems.     

Scheduling prowler training

The U.S. Navy Prowler aircraft is designed for electronic surveillance and countermeasures. In this paper, we describe the problem of scheduling Prowler crew training, and we present two integer programming models to solve it. The first model maximizes the number of aviators trained above 75% in each mission area, subject to the available number of flights, over a single month. The second model distinguishes peacetime from mobilization, and minimizes the number of flights done in mobilization subject to the available number of flights in peacetime. Our models distinguish different types of crew and allow more than one qualification to be earned on a given flight. We give numerical results using real data, comparing our results to the actual readiness of a squadron. We found that crew readiness of Prowler squadrons can be increased by 10%, simply by better scheduling. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 289–305, 2003.     

The impact of superpower arms transfers on conflict in the Middle East

I explore the relationship between superpower arms transfers and the Arab‐Israeli rivalry. My empirical analysis suggests that Soviet arms transfers to the Middle East, more than American transfers, have exacerbated interstate rivalry in the region. It also suggests that Soviet arms transfers, again more than American transfers, have encouraged compensatory arming by the other superpower. These conclusions derive from the results of cross‐correlation analysis, Granger‐causality tests, and variance decompositions, and are quite robust. While my findings paint a rather unflattering portrait of the effects of superpower involvement in the region, they do constitute grounds for optimism in light of current developments.     

ANALYSING DEFENCE DEPENDENCY: THE IMPACT OF THE ROYAL NAVY ON A SUB‐REGIONAL ECONOMY

This paper provides a methodology for estimating the economic impact of defence spending at a sub‐regional level. It does so by calculating the income and employment generated by Britain’s Royal Navy and associated defence activities in the City of Portsmouth and its surrounding area, during the financial year 2003–2004. In an era of military consolidation, the paper offers an insight into the multifaceted impact of defence‐related expenditure. Hence, it presents a generic framework that could prove useful to other researchers when seeking to measure the sub‐regional impact of naval, airforce and army facilities in other national contexts.     

Country Survey I–Military Spending in India 1

After a brief survey of the Indian economy, we survey the supply and demand of military expenditures in India over the last four decades. The causes of military expenditures appear to include regional rivalries and protracted conflicts, but it has proven difficult to delineate these with empirical models. The effects of military spending in India on economic growth appear to be benign, despite much speculation to the contrary. However, the opportunity costs of defence spending are shown to be considerable. We conclude with speculation about the role of debt and debt servicing in retarding future economic growth in India. We also speculate about the potential for the creation of a war economy in India.