A new polynomial algorithm for maximum value flow with an efficient parallel implementation

A new algorithm is presented for finding maximal and maximum value flows in directed single-commodity networks. Commonly algorithms developed for this problem find a maximal flow by gradually augmenting (increasing) a feasible flow to a maximal flow. In the presented algorithm, at the beginning of each step or iteration, the flow on arcs is assigned to flow capacity. This may lead to an infeasible flow violating flow conservation at some nodes. During two passes of a MAIN step, consisting of a forward pass and a backward pass, the flow is reduced on some arcs to regain feasibility. The network is then pruned by omitting saturated arcs, and the process is repeated. The parallel implementation of the algorithm applies the two main steps at the same time to the same network. The outputs of the two steps are compared and the processing continues with the higher feasible flow. The algorithm is simple, intuitive, and efficient. © 1993 John Wiley & Sons, Inc.     

Real-time prediction of projectile penetration to laminates by training machine learning models withfinite element solver as the trainer

Studies on ballistic penetration to laminates is complicated, but important for design effective protection of structures. Experimental means of study is expensive and can often be dangerous. Numerical simu-lation has been an excellent supplement, but the computation is time-consuming. Main aim of this thesis was to develop and test an effective tool for real-time prediction of projectile penetrations to laminates by training a neural network and a decision tree regression model. A large number of finite element models were developed;the residual velocities of projectiles fromfinite element simulations were used as the target data and processed to produce sufficient number of training samples. Study focused on steel 4340tpolyurea laminates with various configurations. Four different 3D shapes of the projectiles were modeled and used in the training. The trained neural network and decision tree model was tested using independently generated test samples using finite element models. The predicted projectile velocity values using the trained machine learning models are then compared with thefinite element simulation to verify the effectiveness of the models. Additionally, both models were trained using a published experimental data of projectile impacts to predict residual velocity of projectiles for the unseen samples. Performance of both the models was evaluated and compared. Models trained with Finite element simulation data samples were found capable to give more accurate predication, compared to the models trained with experimental data, becausefinite element modeling can generate much larger training set, and thus finite element solvers can serve as an excellent teacher. This study also showed that neural network model performs better with small experimental dataset compared to decision tree regression model.     

To Protect and Serve: Civilian Policing and the United Nations Mission in Kosovo

Since the end of the Cold War the process of nation building has become a priority in the attempt to maintain world order and security in the wake of the instability and devastation wrought by failed and war-torn states. The proliferation of nation-building missions has led to their diversification and the need to marshal a vast array of resources in order to attain substantial levels of success. This article deals with a new and important component of peacekeeping and nation-building missions, that of civilian policing. The article outlines the goals of using civilian police officers in nation-building missions and discusses a variety of problems (pragmatic, legal, and cultural) that policing may introduce to such missions. This discussion is focused around the civilian policing component of the United Nations Mission in Kosovo. It delineates the successes and hardships so far experienced during the mission in Kosovo and explores the insights that the mission may provide for similar projects in the future.     

One size does not fit all: personalized incentives in military compensation

A critical element in implementing a compensation scheme including nonmonetary incentives (NMIs) is recognizing that preferences vary widely across Service members. There are at least three sources of variability: across different population classes, across individuals within a population class, and across NMI packages for a particular individual. Surveys across different military communities, ranks, and years of Service show the difficulty of identifying any NMI that has significant value for even 50% of the active duty force. At the same time, approximately 80% of the surveyed Service members expressed a significant positive value for at least one NMI. Therefore, one-size-fits-all incentive packages will not be nearly as effective as more personalized incentive packages. The authors discuss variability in Service member NMI preferences and outline an approach to implementing personalized NMI packages in military compensation through a sealed-bid reverse auction, where Service members select individual NMIs from a “cafeteria-style” menu of options.     

A historical overview of US counter-insurgency

Say not the struggle naught availeth,

The labour and the wounds are vain,

The enemy faints not, nor faileth,

And as things have been, things remain.

Arthur Hugh Clough     

Optimal control of an M/G/1 queue with impatient priority customers

An optimal operating policy is characterized for the infinite‐horizon average‐cost case of a single server queueing control problem. The server may be turned on at arrival epochs or off at departure epochs. Two classes of customers, each of them arriving according to an independent Poisson processes, are considered. An arriving 1‐customer enters the system if the server is turned on upon his arrival, or if the server is on and idle. In the former case, the 1‐customer is selected for service ahead of those customers waiting in the system; otherwise he leaves the system immediately. 2‐Customers remain in the system until they complete their service requirements. Under a linear cost structure, this paper shows that a stationary optimal policy exists such that either (1) leaves the server on at all times, or (2) turns the server off when the system is empty. In the latter case, we show that the stationary optimal policy is a threshold strategy, this feature being commonplace in most of priority queueing systems and inventory models. However, the optimal policy in our model is determined by two thresholds instead of one. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 201–209, 2001