THE ACRS EXPERIENCE AND ITS RELEVANCE TO THE WMDFZ CONFERENCE

This article examines the arms control logic that was applied to the only regional arms control talks that have taken place in the Middle East to date: the Arms Control and Regional Security (ACRS) working group that was part of the multilateral track of the Madrid peace process in the early 1990s. It highlights both the successes and major constraints of the ACRS talks in an effort to assess what might be relevant to the weapons of mass destruction-free zone conference proposed for later this year. In addition to the basic arms control dilemmas that will continue to challenge this conference—as they did ACRS—the article suggests that current conditions in the Middle East are even less conducive to regional dialogue than they were in the earlier period, due to the internal upheavals in several key Arab states, and the specific challenge of Iran's move to develop a military nuclear capability.     

RUSSIAN NAVAL NUCLEAR FUEL AND REACTORS

Russian naval nuclear fuel and reactors pose both proliferation and environmental threats, ranging from the possible theft of highly enriched uranium fuel to the radioactive contamination of the environment, whether due to accident, neglect, or sabotage. Current conditions at Russian naval bases, together with a history of accidents and incidents involving Russia's nuclear fleet, make a convincing case for the large-scale assistance that the G8 is now providing to improve the safety and security of Russian naval reactors and fuel. However, virtually no data has been released to allow accurate, reliable, and independent analysis of reactor and fuel properties, risking misguided international efforts to assist in the areas of nuclear cleanup, nonproliferation, and security. This article identifies and assesses relevant properties and developments related to reactor and fuel design, provides a comprehensive presentation of Russian nuclear naval technologies, and examines technological trends in the context of proliferation and environmental security.     

Sequential learning versus no learning in Bayesian regression models

We consider two regression models: linear and logistic. The dependent variable is observed periodically and in each period a Bayesian formulation is used to generate updated forecasts of the dependent variable as new data is observed. One would expect that including new data in the Bayesian updates results in improved forecasts over not including the new data. Our findings indicate that this is not always true. We show there exists a subset of the independent variable space that we call the “region of no learning.” If the independent variable values for a given period in the future are in this region, then the forecast does not change with any new data. Moreover, if the independent variable values are in a neighborhood of the region of no learning, then there may be little benefit to wait for the new data and update the forecast. We propose a statistical approach to characterize this neighborhood which we call the “region of little learning.” Our results provide insights into the trade‐offs that exist in situations when the decision maker has an incentive to make an early decision based on an early forecast versus waiting to make a later decision based on an updated forecast. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 532–548, 2014     

On the effectiveness of top‐down strategy for forecasting autoregressive demands

We investigate the relative effectiveness of top‐down versus bottom‐up strategies for forecasting the demand of an item that belongs to a product family. The demand for each item in the family is assumed to follow a first‐order univariate autoregressive process. Under the top‐down strategy, the aggregate demand is forecasted by using the historical data of the family demand. The demand forecast for the items is then derived by proportional allocation of the aggregate forecast. Under the bottom‐up strategy, the demand forecast for each item is directly obtained by using the historical demand data of the particular item. In both strategies, the forecasting technique used is exponential smoothing. We analytically evaluate the condition under which one forecasting strategy is preferred over the other when the lag‐1 autocorrelation of the demand time series for all the items is identical. We show that when the lag‐1 autocorrelation is smaller than or equal to 1/3, the maximum difference in the performance of the two forecasting strategies is only 1%. However, if the lag‐1 autocorrelation of the demand for at least one of the items is greater than 1/3, then the bottom‐up strategy consistently outperforms the top‐down strategy, irrespective of the items' proportion in the family and the coefficient of correlation between the item demands. A simulation study reveals that the analytical findings hold even when the lag‐1 autocorrelation of the demand processes is not identical. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007.     

The snowball phenomenon: the US Marine Corps,military mythology and the spread of hybrid warfare theory

ABSTRACT

This article reviews the book by Ofer Fridman and seeks to situate the strategic debate on hybrid war in the context of debate on the US involvement in Iraq. It points to intellectuals from the Marine Corps having a significant role in the initial development of the hybrid warfare concept at a time of some reservation in US military circles over COIN strategy as this was set out in the field manual FM3-24. Thereafter, the hybrid war concept rapidly spread and became a conceptual device used to explain Russian strategic intentions in the aftermath of the invasion of Ukraine in 2014.     

Stochastically minimizing the makespan in flow shops

In this article, we are concerned with scheduling stochastic jobs in a flowshop with m machines and zero intermediate storage. We assume that there are n - 2 identically distributed and 2 fast stochastic jobs. Roughly, the main result states that the makespan is stochastically minimized by placing one of the fast jobs first and the other last.