Simulation of stochastic activity networks using path control variates

This article details several procedures for using path control variates to improve the accuracy of simulation-based point and confidence-interval estimators of the mean completion time of a stochastic activity network (SAN). Because each path control variate is the duration of the corresponding directed path in the network from the source to the sink, the vector of selected path controls has both a known mean and a known covariance matrix. This information is incorporated into estimation procedures for both normal and nonnormal responses. To evaluate the performance of these procedures experimentally, we examine the bias, variance, and mean square error of the controlled point estimators as well as the average half-length and coverage probability of the corresponding confidence-interval estimators for a set of SANs in which the following characteristics are systematically varied: (a) the size of the network (number of nodes and arcs); (b) the topology of the network; (c) the percentage of activities with exponentially distributed durations; and (d) the relative dominance of the critical path. The experimental results show that although large improvements in accuracy can be achieved with some of these procedures, the confidence-interval estimators for normal responses may suffer serious loss of coverage probability in some applications.     

Cumulative search-evasion games

Cumulative search-evasion games (CSEGs) are two-person zero-sum search-evasion games where play proceeds throughout some specified period without interim feedback to either of the two players. Each player moves according to a preselected plan. If (X_t, Y_t,) are the positions of the two players at time t, then the game's payoff is the sum over t from 1 to T of A(X_t, Y_t, t). Additionally, all paths must be “connected.” That is, the finite set of positions available for a player in any time period depends on the position selected by that player in the previous time period. One player attempts to select a mixed strategy over the feasible T-time period paths to maximize the expected payoff. The other minimizes. Two solution procedures are given. One uses the Brown-Robinson method of fictitious play and the other linear programming. An example problem is solved using both procedures.     

Location-allocation for distribution to a uniform demand with transshipments

This article analyzes the location-allocation problem for distribution from a single fixed origin via transshipment terminals to a continuous uniformly distributed demand. Distribution through terminals concentrates flows on the origin-to-terminal links and transportation economies of scale encourage the use of larger vehicles. Analytical expressions are derived for the optimal terminal locations, the optimal allocation of destinations to terminals, and the optimal transportation cost. Continuous analytic models assume either an allocation, by partitioning the service region into sectors, or terminal locations. This is unlikely to produce an optimal distribution system. The optimal cost is compared to the cost for suboptimal location-allocation combinations. Results indicate that the location decision is not too important if destinations are allocated optimally and that allocation to the nearest terminal may be poor, even with optimal locations. © 1992 John Wiley & Sons, Inc.     

Clinical Characterization of Insomnia among Veterans with PTSD: Identifying Risk Factors for Diagnosis and Treatment with Sedative-Hypnotics

Abstract

Insomnia is prevalent among Veterans with post-traumatic stress disorder (PTSD), it exacerbates PTSD symptoms, and it contributes to impaired functioning and quality of life. To improve treatment outcomes, it is important to identify risk factors for insomnia and sedative-hypnotic use. Classification and regression trees and logistic regression models were used to identify variables associated with insomnia or sedative-hypnotic use. Key findings include low insomnia diagnosis rates (3.5–5.6%) and high rates of sedative-hypnotics (44.2–49.0%). Younger Veterans and those without a breathing-related sleep disorder (BRSD) were more likely to receive an insomnia diagnosis. Veterans with greater service connection and those with an alcohol/substance use disorder were more likely to be prescribed sedative-hypnotics. Interaction terms may have identified potential groups at risk of being under-diagnosed with insomnia (i.e. non-black Veterans with psychiatric co-morbidity, black Veterans without psychiatric co-morbidity) as well as groups at risk for sedative-hypnotic use (i.e. younger Veterans without BRSD). In sum, Veterans with PTSD have high rates of sedative-hypnotic use despite minimal evidence they are effective. This is counter to recommendations indicating behavioral interventions are the first-line treatment. Policy changes are needed to reduce use of sedative-hypnotics and increase access to behavioral insomnia interventions.     

Robustness of preallocated preferential defense with assumed attack size and perfect attacking and defending weapons

The problem is to protect a set of t targets by n perfect interceptors against an attack by m perfect weapons. If the defender solves for an optimal preallocated preferential defense and associated game value assuming m₁ attackers, and the attacker knows the assumption of the defender and utilizes m₂ attackers, he may be able to achieve significantly more damage than had the defender assumed that there would be m₂ attackers. The article treats the robustness of preallocated preferential defense to assumptions about the size of the attack and presents results of an alternative approach.     

(Re-)emergent orders: understanding the negotiation(s) of rebel governance

Abstract

The concept of order is often neglected in the study of conflict – seemingly such a ‘disordering’ process. With the recent increase in the examination of rebel governance however, bringing order back into our understanding of rebel and insurgent groups has much to offer in exploring the everyday politics which connect authorities, rebel movements and the population itself, in a complex mass of intersubjective and power-based interactions and negotiations. Rebels both shape and are shaped by existing forms of order in complex and ongoing ways. This article explores how varying elements interact in the negotiation, framing and enforcement of order and develops an original analytical framework to examine the perpetual negotiations of rebel movements in their attempts to cement their control.     

Counterinsurgency American style: Considering David Petraeus and twenty-first century irregular war

This article examines the complex legacy of David Petraeus who was a key figure in the emergence of the US military shift towards counterinsurgency doctrine in the years after 2006. Although Petraeus has been perceived by critics as a publicity seeker, he can be credited with laying the foundations for a more serious commitment to COIN involving in particular in integrating conventional and Special Forces in arenas like village stability operations. The article looks a Petraeus's role in both Iraq and Afghanistan: it concludes that, in the case of Afghanistan, it is too early to assess whether counterinsurgency has had a decisive impact of the outcome of the war against the Taliban.     

Optimization of strategic defenses to provide specified post-attack production capacities

This paper presents a model for choosing a minimum-cost mix of strategic defenses to assure that specified production capacities for several economic sectors survive after a nuclear attack. The defender selects a mix of strategic defenses for each of several geographic regions. The attacker chooses an allocation of attacking weapons to geographic regions, within specified weapon inventories. The attack is optimized against any economic sector. This formulation allows the defense planner the capability to assess the results of the optimal defense structure for a “worst case” attack. The model is a mathematical program with nonlinear programming problems in the constraints; an example of its application is given and is solved using recently developed optimization techniques.