A dynamic general linear model for inference from accelerated life tests

We present a new approach for inference from accelerated life tests. Our approach is based on a dynamic general linear model setup which arises naturally from the accelerated life-testing problem and uses linear Bayesian methods for inference. The advantage of the procedure is that it does not require large numbers of items to be tested and that it can deal with both censored and uncensored data. We illustrate the use of our approach with some actual accelerated life-test data. © 1992 John Wiley & Sons, Inc.     

Performance of N machine centers of K-out-of-M: G type maintained by a single repairman

We consider a system of N (nonsymmetric) machine centers of the K-out-of-M : G type that are maintained by a single repairman. [A machine center functions if and only if at least K of the M machines belonging to the center are good (G).] Such systems are commonly found in various manufacturing and service industries. A stochastic model is developed that accommodates generally distributed repair times and repairman walk times, and most repair scheduling disciplines. K-out-of-M : G type systems also appear as a modeling paradigm in reliability analysis and polling systems performance analysis. Several performance measures are derived for machine-repair systems having K-out-of-M-type centers. A simple example system is developed in detail that exposes the computations involved in modeling applications. © 1992 John Wiley & Sons, Inc.     

Fire truck relocation during major incidents

The effectiveness of a fire department is largely determined by its ability to respond to incidents in a timely manner. To do so, fire departments typically have fire stations spread evenly across the region, and dispatch the closest truck(s) whenever a new incident occurs. However, large gaps in coverage may arise in the case of a major incident that requires many nearby fire trucks over a long period of time, substantially increasing response times for emergencies that occur subsequently. We propose a heuristic for relocating idle trucks during a major incident in order to retain good coverage. This is done by solving a mathematical program that takes into account the location of the available fire trucks and the historic spatial distribution of incidents. This heuristic allows the user to balance the coverage and the number of truck movements. Using extensive simulation experiments we test the heuristic for the operations of the Fire Department of Amsterdam‐Amstelland, and compare it against three other benchmark strategies in a simulation fitted using 10 years of historical data. We demonstrate substantial improvement over the current relocation policy, and show that not relocating during major incidents may lead to a significant decrease in performance.     

Interdiction models for delaying adversarial attacks against critical information technology infrastructure

Information technology (IT) infrastructure relies on a globalized supply chain that is vulnerable to numerous risks from adversarial attacks. It is important to protect IT infrastructure from these dynamic, persistent risks by delaying adversarial exploits. In this paper, we propose max‐min interdiction models for critical infrastructure protection that prioritizes cost‐effective security mitigations to maximally delay adversarial attacks. We consider attacks originating from multiple adversaries, each of which aims to find a “critical path” through the attack surface to complete the corresponding attack as soon as possible. Decision‐makers can deploy mitigations to delay attack exploits, however, mitigation effectiveness is sometimes uncertain. We propose a stochastic model variant to address this uncertainty by incorporating random delay times. The proposed models can be reformulated as a nested max‐max problem using dualization. We propose a Lagrangian heuristic approach that decomposes the max‐max problem into a number of smaller subproblems, and updates upper and lower bounds to the original problem via subgradient optimization. We evaluate the perfect information solution value as an alternative method for updating the upper bound. Computational results demonstrate that the Lagrangian heuristic identifies near‐optimal solutions efficiently, which outperforms a general purpose mixed‐integer programming solver on medium and large instances.     

National restrictions in multinational military operations: A conceptual framework

Recent scholarship in security studies has started to explore the causes and consequences of various forms of national restrictions in multinational military operations (MMOs). This article makes a conceptual contribution to this literature by developing a theoretical framework of national restrictions in MMOs that distinguishes between structural, procedural, and operational restrictions. I argue that these types of restrictions are governed by different causal mechanisms. Structural restrictions are relatively stable over time and effect deployment decisions irrespective of other factors. Procedural restrictions, on the other hand, can constitute veto points against deployment only in combination with distinct political preferences. Finally, operational restrictions directly affect the rules of engagement of troop contributing countries. The article illustrates the three types of restrictions and their interaction with empirical examples from a range of countries and sketches their impact on MMO deployment decisions and mandates.     

The politics of multinational military operations

Today, few countries fight alone; most fight as allies or partners in multilateral campaigns. The end of the Cold War opened a window of opportunity for multinational military operations (MMOs). These have seen varying degrees of participation, enthusiasm, and success. This special forum is devoted to the politics of multilateral warfare including their formation, maintenance, and durability. The introduction sketches past research and derives some key questions of continuing relevance. The contributions shed light on the domestic and international politics of MMOs, focusing on the implementation of national restrictions and their repercussions for MMOs, party politics of military intervention, the conditions under which states decide to defect from military operations, and the role of junior partners in MMOs. In sum, this forum offers a fresh look at the politics of MMOs, including conceptual contributions to the study of national restrictions, domestic constraints, and coalition warfare.     

Mean residual life of coherent systems consisting of multiple types of dependent components

Mean residual life is a useful dynamic characteristic to study reliability of a system. It has been widely considered in the literature not only for single unit systems but also for coherent systems. This article is concerned with the study of mean residual life for a coherent system that consists of multiple types of dependent components. In particular, the survival signature based generalized mixture representation is obtained for the survival function of a coherent system and it is used to evaluate the mean residual life function. Furthermore, two mean residual life functions under different conditional events on components’ lifetimes are also defined and studied.     

Keeping an eye on South Asian skies: America’s pivotal deterrence in nuclearized India–Pakistan crises

Since declaring their nuclear weapons capabilities in 1998, India and Pakistan have engaged in three major crises that each threatened to escalate into war. In each crisis, the USA engaged in active diplomacy to dissuade the South Asian rivals from taking escalatory actions. Previous literature on the crises has described the American role, but has not theorized third-party involvement in a nuclearized regional rivalry. We apply Timothy Crawford’s pivotal deterrence theory to the nuclearized India–Pakistan conflict, and extend the original theory to cover the novel condition of a non-superpower nuclear dyad, in the context of a single-superpower international system. We find that America’s pivotal deterrence generally enhanced stability in the India–Pakistan crises, and unlike in pre-nuclear South Asia, other great powers supported American diplomacy. However, we suggest that future regional crises between nuclear rivals, in South Asia or elsewhere, may present greater challenges for pivotal deterrence.     

Growth recovery after civil conflict: a fractional integration approach

Using recent econometric techniques based on fractional integration, we find that developing countries recover their economic growth faster than developed countries in response to a shock. Following this methodology, we find that longer civil conflicts are associated with a faster recovery process. We further investigate this issue by exploring correlations with components of GDP, military spending, institutions and aid and find heterogeneous effects of these channels by duration of conflict. Higher government spending is correlated with faster recoveries post longer conflicts, and higher consumption spending is linked to faster recoveries following shorter conflicts. Military spending appears to be driving the government expenditure that makes countries recover from longer conflicts. More democratic institutions are associated with faster recoveries post short wars but slower recoveries following long wars.     

Estimating the probability that a simulated system will be the best

Consider a stochastic simulation experiment consisting of v independent vector replications consisting of an observation from each of k independent systems. Typical system comparisons are based on mean (long‐run) performance. However, the probability that a system will actually be the best is sometimes more relevant, and can provide a very different perspective than the systems' means. Empirically, we select one system as the best performer (i.e., it wins) on each replication. Each system has an unknown constant probability of winning on any replication and the numbers of wins for the individual systems follow a multinomial distribution. Procedures exist for selecting the system with the largest probability of being the best. This paper addresses the companion problem of estimating the probability that each system will be the best. The maximum likelihood estimators (MLEs) of the multinomial cell probabilities for a set of v vector replications across k systems are well known. We use these same v vector replications to form v^k unique vectors (termed pseudo‐replications) that contain one observation from each system and develop estimators based on AVC (All Vector Comparisons). In other words, we compare every observation from each system with every combination of observations from the remaining systems and note the best performer in each pseudo‐replication. AVC provides lower variance estimators of the probability that each system will be the best than the MLEs. We also derive confidence intervals for the AVC point estimators, present a portion of an extensive empirical evaluation and provide a realistic example. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 341–358, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10019