Why nations fail: defense spending,fighting commitment and,inter-nations-prosperity-poverty-gap

Both the increasing defense spending and the widening divergence between rich and poor countries are of great concerns. This paper attempts to explain the two concepts in a unify theory framework. In the view of conflict economics, a nation’s defense spending can be seen as the fighting commitment of distributive effort in the global economy while other is the productive effort. The development of global economy needs the productive efforts from almost every nation, and the distribution of the aggregate output is determined in large degree by the fighting commitment of each nation. The numerical simulation of the model gives a reasonable explanation of the patterns of the divergence/convergence of prosperity-poverty gap between nations, the fact which is evidenced by many empirical analyses. (1) Given the initial wealth ratio between nations fixed, there is a critical value of fighting decisiveness, when the actual value is larger than the critical value, it is more likely to result in Matthew effect; otherwise the gap would gradually be shortened. (2) Given the fighting decisiveness fixed, there is a critical value of initial wealth ratio, when the actual value is larger than the critical value, it is more likely to result in Matthew effect; otherwise, the gap would gradually be shortened. The study gives a new perspective to explain and handle the increasingly defense spending and the prosperity-poverty gap between nations.     

Doubly Stochastic Sequential Assignment Problem

This article introduces the Doubly Stochastic Sequential Assignment Problem (DSSAP), an extension of the Sequential Stochastic Assignment Problem (SSAP), where sequentially arriving tasks are assigned to workers with random success rates. A given number of tasks arrive sequentially, each with a random value coming from a known distribution. On a task arrival, it must be assigned to one of the available workers, each with a random success rate coming from a known distribution. Optimal assignment policies are proposed for DSSAP under various assumptions on the random success rates. The optimal assignment algorithm for the general case of DSSAP, where workers have distinct success rate distribution, has an exponential running time. An approximation algorithm that achieves a fraction of the maximum total expected reward in a polynomial time is proposed. The results are illustrated by several numerical experiments. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 124–137, 2016     

Manpower allocation with time windows and job‐teaming constraints

In this work, we study manpower allocation with time windows and job‐teaming constraints. A set of jobs at dispersed locations requires teams of different types of workers where each job must be carried out in a preestablished time window and requires a specific length of time for completion. A job is satisfied if the required composite team can be brought together at the job's location for the required duration within the job's time window. The objective is to minimize a weighted sum of the total number of workers and the total traveling time. We show that construction heuristics used with simulated annealing is a good approach to solving this NP‐hard problem. In experiments, this approach is compared with solutions found using CPLEX and with lower bounds obtained from a network flow model. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

A Lanchester-type aggregated-force model of conventional ground combat

This article develops a Lanchester-type model of large-scale conventional ground combat between two opposing forces in a “sector”. It is shown that nonlinear Helmbold-type equations of warfare with operational losses may be used to represent the loss-rate curves that have been used in many aggregated-force models. These nonlinear differential equations are used to model the attrition of combat capability (as quantified by a so-called firepower index) in conjunction with a rate-of-advance equation that relates motion of the contact zone (or FEBA) between the opposing forces to the force ratio and tactical decisions of the combatants. This simplified auxiliary model is then used to develop some important insights into the dynamics of FEBA movement used in large-scale aggregated-force models. Different types of behavior for FEBA movement over time are shown to correspond to different ranges of values for the initial force ratio, for example, an attack will “stall out” for a range of initial force ratios above a specific threshold value, but it will “break out” for force ratios above a second specific threshold value. Such FEBA-movement predictions are essentially based on being able to forecast changes over time in the force ratio.     

论科技劳动与价值创造

在知识经济条件下 ,科学技术迅猛发展 ,而科技创新劳动能够推动生产力飞速发展 ,是一种推动和实现科技重大质的飞跃的劳动 ,是具有科学知识高积累和高创造性能力的科技人才进行的生产劳动 ,是具有高度创造性、极其复杂的劳动 ,是创造价值的巨大源泉。科技劳动是劳动价值论的重要范畴 ,深入研究它在价值创造中的重大作用具有深刻的理论和现实意义。     

Optimal replacement under additive damage and other failure models

A machine or production system is subject to random failure. Upon failure the system is replaced by a new one, and the process repeats. A cost is associated with each replacement, and an additional cost is incurred at each failure in service. Thus, there is an incentive for a controller to attempt to replace before failure occurs. The problem is to find an optimal control strategy that balances the cost of replacement with the cost of failure and results in a minimum total long-run average cost per unit time. We attack this problem under the cumulative damage model for system failure. In this failure model, shocks occur to the system in accordance with a Poisson process. Each shock causes a random amount of damage or wear and these damages accumulate additively. At any given shock, the system fails with a known probability that depends on the total damage accumulated to date. We assume that the cumulative damage is observable by the controller and that his decisions may be based on its current value. Supposing that the shock failure probability is an increasing function of the cumulative damage, we show that an optimal policy is to replace either upon failure or when this damage first exceeds a critical control level, and we give an equation which implicitly defines the optimal control level in terms of the cost and other system parameters. Also treated are some more general models that allow for income lost during repair time and other extensions.     

Optimal replacement of continuously degrading systems in partially observed environments

Motivated by wind energy applications, we consider the problem of optimally replacing a stochastically degrading component that resides and operates in a partially observable environment. The component's rate of degradation is modulated by the stochastic environment process, and the component fails when it is accumulated degradation first reaches a fixed threshold. Assuming periodic inspection of the component, the objective is to minimize the long‐run average cost per unit time of performing preventive and reactive replacements for two distinct cases. The first case examines instantaneous replacements and fixed costs, while the second considers time‐consuming replacements and revenue losses accrued during periods of unavailability. Formulated and solved are mixed state space, partially observable Markov decision process models, both of which reveal the optimality of environment‐dependent threshold policies with respect to the component's cumulative degradation level. Additionally, it is shown that for each degradation value, a threshold policy with respect to the environment belief state is optimal if the environment alternates between two states. The threshold policies are illustrated by way of numerical examples using both synthetic and real wind turbine data. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 395–415, 2015     

Threshold incentives over multiple periods and the sales hockey stick phenomenon

In this article, we study threshold‐based sales‐force incentives and their impact on a dealer's optimal effort. A phenomenon, observed in practice, is that the dealer exerts a large effort toward the end of the incentive period to boost sales and reach the threshold to make additional profits. In the literature, the resulting last‐period sales spike is sometimes called the hockey stick phenomenon (HSP). In this article, we show that the manufacturer's choice of the incentive parameters and the underlying demand uncertainty affect the dealer's optimal effort choice. This results in the sales HSP over multiple time periods even when there is a cost associated with waiting. We then show that, by linking the threshold to a correlated market signal, the HSP can be regulated. We also characterize the variance of the total sales across all the periods and demonstrate conditions under the sales variance can be reduced. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Manpower modeling in cost effectiveness studies of usaf program to reduce the incidence of heart disease

Planning for a cardiovascular disease reduction program, soon to be initiated by the United States Air Force, has required an evaluation of its expected cost effectiveness. During the course of this evaluation, it was necessary to consider manpower flows and their expected changes in response to the disease reduction program. This paper describes several manpower models that were applied: a simple expected value equilibrium model; a cross-sectional model that considered the length of service of personnel; and a staffing model used to optimize the allocation of paramedics to the many Air Force bases of various sizes. The relevance of these models to the cost effectiveness evaluation is shown but the detailed cost effectiveness results are not presented.     

A single-machine replacement model with learning

The replacement or upgrade of productive resources over time is an important decision for a manufacturing organization. The type of technology used in the productive resources determines how effectively the manufacturing operations can support the product and marketing strategy of the organization. Increasing operating costs (cost of maintenance, labor, and depreciation) over time force manufacturing organizations to periodically consider replacement or upgrade of their existing productive resources. We assume that there is a setup cost associated with the replacement of a machine, and that the setup cost is a nonincreasing function of the number of replacements made so far due to learning in setups. The operating cost of a newer machine is assumed to be lower than the operating cost of an older machine in any given period, except perhaps in the first period of operation of the new machine when the cost could be unusually high due to higher initial depreciation. A forward dynamic programming algorithm is developed which can be used to solve finite-horizon problems. We develop procedures to find decision and forecast horizons such that choices made during the decision horizon based only on information over the forecast horizon are also optimal for any longer horizon problem. Thus, we are able to obtain optimal results for what is effectively an infinite-horizon problem while only requiring data over a finite period of time. We present a numerical example to illustrate the decision/forecast horizon procedure, as well as a study of the effects of considering learning in making a series of machine replacement decisions. © 1993 John Wiley & Sons. Inc.     

The knapsack problem with a minimum filling constraint

We study a knapsack problem with an additional minimum filling constraint, such that the total weight of selected items cannot be less than a given threshold. The problem has several applications in shipping, e‐commerce, and transportation service procurement. When the threshold equals the knapsack capacity, even finding a feasible solution to the problem is NP‐hard. Therefore, we consider the case when the ratio α of threshold to capacity is less than 1. For this case, we develop an approximation scheme that returns a feasible solution with a total profit not less than (1 ‐ ε) times the total profit of an optimal solution for any ε > 0, and with a running time polynomial in the number of items, 1/ε, and 1/(1‐α). © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

Optimal maintenance policy for stochastically failing equipment: A diffusion approximation

A system receives shocks at random points of time. Each shock causes a random amount of damage which accumulates over time. The system fails when the accumulated damage exceeds a fixed threshold. Upon failure the system is replaced by a new one. The damage process is controlled by means of a maintenance policy. There are M possible maintenance actions. Given that a maintenance action m is employed, then the cumulative damage decreases at rate r^m. Replacement costs and maintenance costs are considered. The objective is to determine an optimal maintenance policy under the following optimality criteria: (1) long-run average cost; (2) total expected discounted cost over an infinite horizon. For a diffusion approximation, we show that the optimal maintenance expenditure rate is monotonically increasing in the cumulative damage level.     

模糊Petri网在故障诊断知识表示和推理中的应用

针对传统的模糊产生式规则知识表示复杂、推理效率低、单一阈值设定不能满足复杂故障诊断需求的问题,给出了模糊产生式规则转换为模糊Petri网的一般方法和故障诊断模型,以及基于双阈值设定的两级故障诊断推理算法,并将其应用于某型柴油机遥控系统故障诊断之中。通过设置双阈值提高了故障诊断的推理速度和推理效率,同时又能对系统的准故障状态进行检测,及时发现潜在故障,排除故障隐患。     

基于差分和神经网络的同步辐射光源图像压缩方法

针对常见的图像无损压缩方法效果不佳问题,提出了一种基于图像差分和神经网络的同步辐射光源图像无损压缩方法。通过图像差分以减少图像序列内部的线性相关性,训练神经网络模型以学习图像序列内部的非线性相关性,得到预测概率分布,结合算术编码压缩。为加速预测和编码过程,将像素值按位分裂为两部分进行并行处理。基于上海同步辐射光源图像的测试表明,相较于便携式网络图形、JPEG2000和自由无损图像格式等,该方法可将压缩率提升20%以上,像素位分裂可以缩短30%的模型预测和编码时间。     

A manpower planning/capital budgeting model (MAPCAB)

A deterministic resource allocation model is developed to optimize defense effectiveness subject to budget, manpower, and risk constraints. The model consists of two major submodels connected by a heuristic. The first is a mathematical program which optimizes the multiperiod weapon mix subject to the constraint set. The second is a manpower supply model based on a transition matrix in which individual transitions are functions of personnel related budgets and historical transition rates. The heuristic marries the submodels through an iterative process leading to improved solutions. An example is provided which demonstrates how systems are undercosted and overprocured if manpower supply is not properly reflected relative to manpower demand.     

Themes in defence manpower economics and challenges for the future

Raising and maintaining military forces have posed enormous challenges for the United States and its allies. Economists have made significant contributions to understanding of how to recruit and manage such forces. This paper highlights key past contributions and discusses challenges for future research. Rapid changes in the roles and missions of military personnel, technology, and the civilian labor market pose serious challenges for future military manpower policy and will challenge economists to develop new approaches to military recruiting and personnel management. Yet the body of past research can continue to provide insight and guidance in making decisions about defense manpower.     

A multiple‐shift workforce scheduling model under annualized hours

Many manufacturing and service organizations in Europe have used annualized hours, also known as flexiyear, to successfully tackle seasonal demand. Under annualized hours, the employer has a certain number of labor hours available in a year and the employer can allocate the hours over the year according to manpower need. A problem in planning for annualized hours is the scheduling of the workforce over the year. We present an algorithm to generate an annual schedule for a scenario in which a facility operates one or more shifts and manpower need may vary from week to week. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 726–736, 1999     

The timing of contests

We develop a simple model to analyze the timing of contests. When the odds of winning a contest are exogenously given – we show that if either the players discount the future or if the total cost of contest is smaller in the future – there exist subgame perfect equilibria where both players settle, anticipating a contest in the future. With endogenous efforts, the aggregate efforts expanded in a contest are smaller if the contest occurs in the future when the relative effort productivities remain constant or diverge over time, thus creating scope for delay in contests. When the effort productivities converge over time, the total efforts may be greater under a future contest. As a consequence, players either settle over the two periods, or else they initiate a contest immediately.     

Longitudinal manpower planning models

A manpower planning model is presented that exploits the longitudinal stability of manpower cohorts. The manpower planning process is described. An infinite horizon linear program for calculating minimum cost manpower input plans is presented and found to have a straightforward solution in a great many cases and to yield an easily implemented approximation technique in other cases.     

Short-term retrenchment planning in hierarchical manpower systems

We address the issue of short-term retrenchment planning required of organizations that are phasing down their manpower levels at rates faster than are allowed by natural attrition. Specifically, the problem we study is as follows: given the initial and target grade populations in a hierarchical manpower system at the end of a finite time horizon and the per-period rate of natural attrition for each grade, find a stationary manpower policy that minimizes the maximum per-period rate of retrenchment across all the grades over all stationary policies that yield the target grade populations at the end of the horizon. Because the problem is a nonconvex, nonseparable, nonlinear program, we develop a heuristic in which the promotion proportions of all the grades are successively fixed, starting from the lowest grade. We prove optimality of the heuristic policy in three nontrivial situations. In a computational experiment, in 135 out of 150 randomly generated instances (i.e., in 90% of the cases), the heuristic yielded a solution that was as good or better than that yielded by a benchmark computer program that solves the present problem as a nonlinear program. Further, the average computational time under the heuristic was an order of magnitude less than that under the program. © 1995 John Wiley & Sons, Inc.