Institutions,information, and commitment: the role of democracy in conflict

This paper explores the hypothesis that both the preexisting quality of democracy in a polity at the onset of conflict and the quality of democracy expected to emerge in the aftermath influence the likelihood of civil war. An empirical investigation of the hypothesis presents a challenge due to concerns of endogeneity and selection: the post-conflict level of democracy is endogenous to the pre-conflict level. Further, for a given time period, either a number of countries have not experienced civil war; or if they did, did not resolve the conflict. We overcome this selection bias by implementing a three-step extension to the Heckman procedure using an unbalanced cross-country panel of 77 countries over the period 1971–2005. Consistent with our hypothesis, we find that a standard deviation improvement in the existing level of democracy reduces the probability of civil war by approximately 9 percentage points and a corresponding improvement in expected post-conflict democratization increases the probability of conflict by approximately 48 percentage points.     

NATO’s push into the Caucasus: geopolitical flashpoints and limits for expansion

The Caucasus has been a major flashpoint of contention between NATO and a resurgent Russia since the collapse of the Soviet Union. The rivalry saw the escalation of hostility in the region during the brief 2008 Russo-Georgian War where a NATO-backed Georgia challenged South Ossetia supported by the Russian military. In 2011, NATO officially recognised Georgia as a potential member, challenging Russia’s traditional sphere of influence in the Caucasus. Moscow says the Eastward expansion of NATO into the Baltics and to include Georgia as a member state is a method of containing a resurgent Russia. However, the former Soviet Republics of Ukraine, the Baltics and Georgia, maintain that Russia represents a threat to their sovereignty, as seen by the Russian support of the breakaway unrecognised Republics of South Ossetia and Abkhazia. A hostile rivalry between the Russian-backed Armenia and Azerbaijan, which is reliant upon NATO-member Turkey, intensifies the polarisation in the Caucasus.     

Life in the “Gray Zone”: observations for contemporary strategists

The term “Gray Zone” is gaining in popularity as a way of describing contemporary security challenges. This article describes the “short-of-war” strategies – the fait accompli, proxy warfare, and the exploitation of ambiguous deterrence situations, i.e. “salami tactics” – that are captured by the term and offers several explanations for why state and non-state actors are drawn to these strategies. The analysis highlights why defense postures based on deterrence are especially vulnerable to the short-of-war strategies that populate the “Gray Zone.” The article concludes by suggesting how defense officials might adapt defense policies to life in the “Gray Zone.”     

Using multiple searchers in constrained-path,moving-target search problems

The search theory open literature has paid little, if any, attention to the multiple-searcher, moving-target search problem. We develop an optimal branch-and-bound procedure and six heuristics for solving constrained-path problems with multiple searchers. Our optimal procedure outperforms existing approaches when used with only a single searcher. For more than one searcher, the time needed to guarantee an optimal solution is prohibitive. Our heuristics represent a wide variety of approaches: One solves partial problems optimally, two use paths based on maximizing the expected number of detections, two are genetic algorithm implementations, and one is local search with random restarts. A heuristic based on the expected number of detections obtains solutions within 2% of the best known for each one-, two-, and three-searcher test problem considered. For one- and two-searcher problems, the same heuristic's solution time is less than that of other heuristics. For three-searcher problems, a genetic algorithm implementation obtains the best-known solution in as little as 20% of other heuristic solution times. © 1996 John Wiley & Sons, Inc.     

Distance-directed augmenting path algorithms for maximum flow and parametric maximum flow problems

Until recently, fast algorithms for the maximum flow problem have typically proceeded by constructing layered networks and establishing blocking flows in these networks. However, in recent years, new distance-directed algorithms have been suggested that do not construct layered networks but instead maintain a distance label with each node. The distance label of a node is a lower bound on the length of the shortest augmenting path from the node to the sink. In this article we develop two distance-directed augmenting path algorithms for the maximum flow problem. Both the algorithms run in O(n²m) time on networks with n nodes and m arcs. We also point out the relationship between the distance labels and layered networks. Using a scaling technique, we improve the complexity of our distance-directed algorithms to O(nm log U), where U denotes the largest arc capacity. We also consider applications of these algorithms to unit capacity maximum flow problems and a class of parametric maximum flow problems.     

Evaluation of base-stock policies in multiechelon inventory systems with compound-poisson demands

This article analyzes a model of a multiechelon inventory system: The exogenous demands form independent compound-Poisson processes. Each location follows a base-stock policy. The transit times between locations may be stochastic. Instead of assuming independent transit times, we follow an approach closer to the standard treatment of single-location models. We develop procedures to compute steady-state performance measures, including average backorders and average inventories. The model and the analysis generalize those of Svoronos and Zipkin, who treat the case of pure Poisson demands.     

Optimal cutoff strategies in capacity expansion problems

Capacity expansion refers to the process of adding facilities or manpower to meet increasing demand. Typical capacity expansion decisions are characterized by uncertain demand forecasts and uncertainty in the eventual cost of expansion projects. This article models capacity expansion within the framework of piecewise deterministic Markov processes and investigates the problem of controlling investment in a succession of same type projects in order to meet increasing demand with minimum cost. In particular, we investigate the optimality of a class of investment strategies called cutoff strategies. These strategies have the property that there exists some undercapacity level M such that the strategy invests at the maximum available rate at all levels above M and does not invest at any level below M. Cutoff strategies are appealing because they are straightforward to implement. We determine conditions on the undercapacity penalty function that ensure the existence of optimal cutoff strategies when the cost of completing a project is exponentially distributed. A by-product of the proof is an algorithm for determining the optimal strategy and its cost. © 1995 John Wiley & Sons, Inc.     

Equipment replacement under technological change

For infinite-horizon replacement economy problems it is common practice to truncate the problem at some finite horizon. We develop bounds on the error due to such a truncation. These bounds differ from previous results in that they include both revenues and costs. Bounds are illustrated through a numerical example from a real case in vehicle replacement. © 1994 John Wiley & Sons, Inc.