An empirical assessment of us air force

The US Air Force is facing a record shortfall in pilots over the coming decade. Using personnel data on more than 10,000 Air Force pilots, this study examines the factors affecting the retention of pilots and assesses the effectiveness of the pilot bonus programme implemented by the Air Force to reduce attrition. Although surveys indicated sustained deployment rates were the leading cause of job dissatisfaction among Air Force pilots, the results of this study suggest economic factors had the largest impact on retention.     

A stochastic air combat logistics decision model for Blue versus Red opposition

Technologically advanced aircraft rely on robust and responsive logistics systems to ensure a high state of operational readiness. This paper fills a critical gap in the literature for combat models by closely relating effectiveness of the logistics system to determinants of success in combat. We present a stochastic diffusion model of an aerial battle between Blue and Red forces. The number of aircraft of Blue forces aloft and ready to be aloft on combat missions is limited by the maximum number of assigned aircraft, the reliability of aircraft subsystems, and the logistic system's ability to repair and replenish those subsystems. Our parsimonious model can illustrate important trade‐offs between logistics decision variables and operational success.     

Group testing procedures with quantitative features and incomplete identification

We present a group testing model for items characterized by marker random variables. An item is defined to be good (defective) if its marker is below (above) a given threshold. The items can be tested in groups; the goal is to obtain a prespecified number of good items by testing them in optimally sized groups. Besides this group size, the controller has to select a threshold value for the group marker sums, and the target number of groups which by the tests are classified to consist only of good items. These decision variables have to be chosen so as to minimize a cost function, which is a linear combination of the expected number of group tests and an expected penalty for missing the desired number of good items, subject to constraints on the probabilities of misclassifications. We treat two models of this kind: the first one is based on an infinite population size, whereas the second one deals with the case of a finite number of available items. All performance measures are derived in closed form; approximations are also given. Furthermore, we prove monotonicity properties of the components of the objective function and of the constraints. In several examples, we study (i) the dependence of the cost function on the decision variables and (ii) the dependence of the optimal values of the decision variables (group size, group marker threshold, and stopping rule for groups classified as clean) and of the target functionals (optimal expected number of tests, optimal expected penalty, and minimal expected cost) on the system parameters.© 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

An MX/G/1 queueing system with disasters and repairs under a multiple adapted vacation policy

We consider a queueing system with batch Poisson arrivals subject to disasters which occur independently according to a Poisson process but affect the system only when the server is busy, in which case the system is cleared of all customers. Following a disaster that affects the system, the server initiates a repair period during which arriving customers accumulate without receiving service. The server operates under a Multiple Adapted Vacation policy. The stationary regime of this process is analyzed using the supplementary variables method. We obtain the probability generating function of the number of customers in the system, the fraction of customers who complete service, and the Laplace transform of the system time of a typical customer in stationarity. The stability condition for the system and the Laplace transform of the time between two consecutive disasters affecting the system is obtained by analyzing an embedded Markov renewal process. The statistical characteristics of the batches that complete service without being affected by disasters and those of the partially served batches are also derived. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 171–189, 2015     

精密机床导轨的测量分析

本文提出了一个用于质量诊断的精密机床导轨分析系统。受控目标的质量评估是依据于对一个物体在选定区间内的测量形状与位置偏差来确定的。质量评估采用相关综合指标的形式:基本误差函数,综合不平行度。在对完整的支撑部件或导向部件作评估的时候,这套系统能对各部件的位置做校正。本文所描述的计算机系统能控制任何测量系统。目前的版本是控制一个测量平动与转动位移量的激光干涉仪。     

Testing or fault-finding for reliability growth: A missile destructive-test example

A new piece of equipment has been purchased in a lot of size m. Some of the items can be used in destructive testing before the item is put into use. Testing uncovers faults which can be removed from the remaining pieces of equipment in the lot. If t < m pieces of equipment are tested, then those that remain, m₁ = m − t, have reduced fault incidence and are more reliable than initially, but m₁ may be too small to be useful, or than is desirable. In this paper models are studied to address this question: given the lot size m, how to optimize by choice of t the effectiveness of the pieces of equipment remaining after the test. The models used are simplistic and illustrative; they can be straightforwardly improved. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 623–637, 1997     

An extremal problem in subconnectivity

The connectivity of a subgraph of a graph can exceed the connectivity of the graph. We call the largest of the connectivities of all subgraphs the subconnectivity. We then give the exact solution to the extremal problem of determining the maximum number of lines in a p-point graph of subconnectivity two.     

The complementary use of regression diagnostics and robust estimators

Regression modeling for prediction or forecasting purposes is critically dependent on the quality of the data which are used to estimate the model parameters. Extreme response or predictor-variable values can substantially influence least-squares estimates and disproportionately affect predictions. Robust alternatives to least-squares are less sensitive to extreme observations and can provide more precise predictions. In this article diagnostic displays are used to identify extreme observations and to assess the sensitivity of least-squares parameter estimates and predictions to the inclusion of these observations in a data set. The displays are shown to aid in the interpretation of weights which robust estimators assign to influential observations.     

The frequency assignment problem: A solution via nonlinear programming

This paper gives a mathematical programming model for the problem of assigning frequencies to nodes in a communications network. The objective is to select a frequency assignment which minimizes both cochannel and adjacent-channel interference. In addition, a design engineer has the option to designate key links in which the avoidance of jamming due to self interference is given a higher priority. The model has a nonconvex quadratic objective function, generalized upper-bounding constraints, and binary decision variables. We developed a special heuristic algorithm and software for this model and tested it on five test problems which were modifications of a real-world problem. Even though most of the test problems had over 600 binary variables, we were able to obtain a near optimum in less than 12 seconds of CPU time on a CDC Cyber-875.