Preventive maintenance at opportunities of restricted duration

This article deals with the problem of setting priorities for the execution of maintenance packages at randomly occurring opportunities. These opportunities are of restricted duration, implying that only a limited number of packages can be executed. The main idea proposed is to set up a model for determining the optimal execution time for the individual maintenance packages and to develop cost criteria for deviations from the optimal time. In this article we use the block replacement model, but the approach can be easily extended to include other optimization models as well. Using Monte Carlo simulation the performance of the method is compared with various heuristics, both for a two-package and a multipackage case. © 1994 John Wiley & Sons, Inc.     

Praying for Rain? Water Scarcity and the Duration and Outcomes of Civil Wars

Recent anecdotal evidence from the civil wars in Somalia and Yemen suggest that water scarcity may shape the dynamics of civil wars. While a considerable body of research has examined the connection between water scarcity (such as low rainfall) and the onset of civil war, very little research has examined how water scarcity may shape the duration and outcomes of civil wars. Looking specifically at rainfall, this paper argues that changes in access to water play a key role in the duration of civil wars. As rainfall declines, there is a reduction in resources available to both the government and the rebel group, leading to a stalemate in fighting. Furthermore, this paper argues that declines in rainfall are felt more acutely by rebel groups who seek to challenge the government through conventional warfare. This paper tests these propositions using hazard models. The results provide robust support for the propositions.     

Maintaining systems with heterogeneous spare parts

We consider the problem of optimally maintaining a stochastically degrading, single‐unit system using heterogeneous spares of varying quality. The system's failures are unannounced; therefore, it is inspected periodically to determine its status (functioning or failed). The system continues in operation until it is either preventively or correctively maintained. The available maintenance options include perfect repair, which restores the system to an as‐good‐as‐new condition, and replacement with a randomly selected unit from the supply of heterogeneous spares. The objective is to minimize the total expected discounted maintenance costs over an infinite time horizon. We formulate the problem using a mixed observability Markov decision process (MOMDP) model in which the system's age is observable but its quality must be inferred. We show, under suitable conditions, the monotonicity of the optimal value function in the belief about the system quality and establish conditions under which finite preventive maintenance thresholds exist. A detailed computational study reveals that the optimal policy encourages exploration when the system's quality is uncertain; the policy is more exploitive when the quality is highly certain. The study also demonstrates that substantial cost savings are achieved by utilizing our MOMDP‐based method as compared to more naïve methods of accounting for heterogeneous spares.     

Decapitation,disruption, and unintended consequences in counterterrorism: lessons from Islamist terror networks in Spain

This study examines the unintended consequences of decapitation strategies. Two Islamist terror networks in Spain have been used to critically evaluate theories of leadership removal guided by large-N cross-sectional research. Arguably, current models neglect to include relational variables that constitute the foundation for policies of network disruption. Spanish terror networks are mapped out over a 10-year period (1995–2004) to demonstrate the importance of network variables. Policies meant to disrupt militant networks can generate unintended consequences, as was the case with Spain’s Operation Dátil following the 9/11 attacks on the Twin Towers and the Pentagon in the United States. The Madrid train bombing network developed in the vacant political space following the counterterrorism operation that targeted radical Islamists in Spain.     

Parallel machine scheduling with batch deliveries to minimize total flow time and delivery cost

Motivated by the flow of products in the iron and steel industry, we study an identical and parallel machine scheduling problem with batch deliveries, where jobs finished on the parallel machines are delivered to customers in batches. Each delivery batch has a capacity and incurs a cost. The objective is to find a coordinated production and delivery schedule that minimizes the total flow time of jobs plus the total delivery cost. This problem is an extension of the problem considered by Hall and Potts, Ann Oper Res 135 (2005) 41–64, who studied a two‐machine problem with an unbounded number of transporters and unbounded delivery capacity. We first provide a dynamic programming algorithm to solve a special case with a given job assignment to the machines. A heuristic algorithm is then presented for the general problem, and its worst‐case performance ratio is analyzed. The computational results show that the heuristic algorithm can generate near‐optimal solutions. Finally, we offer a fully polynomial‐time approximation scheme for a fixed number of machines. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 492–502, 2016     

Optimal strategies for problems of simultaneous attack against an area defense with impact-point prediction

An area to be defended consists of separated point targets. These targets are subject to an attack in which the offensive weapons are assumed to arrive simultaneously. The defense has area defenders, each of which is capable of intercepting any attacker'. Furthermore, the defense has impact-point prediction, i.e., it has knowledge of each attacker's intended target prior to allocation of the area interceptors. For a given attack, the defense wishes to allocate its interceptors against attackers so as to maximize the expected total survival value of the targets. In its first move, the offense seeks an attack allocation which will minimize expected total surviving value against best defense. We develop an algorithm to determine optimal attack and defense strategies and the optimal value of this sequential min-max problem. Branch-and-bound techniques are used to obtain integer solutions, and illustrative computational results are provided.     

The discrete evasion game with three-move lag

The discrete evasion game with three-move lag, formulated over 30 years ago, was one of the earliest games with time-lag complications. This game remains unsolved even though it is well known that the game has a value. In this article we obtain an upper bound for the value by constructing a strategy which consists of 400 conditional probabilities for the minimizing player. This is believed to be the best upper bound known.     

Testing for positive quadrant dependence in ordinal contingency table

Two new randomization tests are introduced for ordinal contingency tables for testing independence against strictly positive quadrant dependence, i.e., P(X > x,Y > y) ≥ P(X > x)P(Y > y) for all x,y with strict inequality for some x and y. For a number of cases, simulation is used to compare the estimated power of these tests versus those standard tests based on Kendall's T, Spearman's p, Pearson's X², the usual likelihood ratio test, and a test based upon the log-odds ratio. In these cases, subsets of the alternative region are identified where each of the testing statistics is superior. The new tests are found to be more powerful than the standard tests over a broad range of the alternative regions for these cases.