军事攻防中的多属性资源分配对策模型

针对资源受限情形下的两阶段攻防资源分配问题,提出一种基于多属性决策的资源分配对策模型。防守者首先将有限的防护资源分配到不同的目标上,继而进攻者选择一种威胁组合方式对目标实施打击。基于博弈论相关知识,模型的求解结果可以使防守者最小化自身损失,使进攻者最大化进攻收益。同时,针对模型的特点,给出了一些推论和证明。通过一个示例验证了模型的合理性以及相关推论的准确性,能够为攻、防双方规划决策提供辅助支持。     

A model of supply-chain decisions for resource sharing with an application to ventilator allocation to combat COVID-19

We present a stochastic optimization model for allocating and sharing a critical resource in the case of a pandemic. The demand for different entities peaks at different times, and an initial inventory for a central agency are to be allocated. The entities (states) may share the critical resource with a different state under a risk-averse condition. The model is applied to study the allocation of ventilator inventory in the COVID-19 pandemic by FEMA to different U.S. states. Findings suggest that if less than 60% of the ventilator inventory is available for non-COVID-19 patients, FEMA's stockpile of 20 000 ventilators (as of March 23, 2020) would be nearly adequate to meet the projected needs in slightly above average demand scenarios. However, when more than 75% of the available ventilator inventory must be reserved for non-COVID-19 patients, various degrees of shortfall are expected. In a severe case, where the demand is concentrated in the top-most quartile of the forecast confidence interval and states are not willing to share their stockpile of ventilators, the total shortfall over the planning horizon (until May 31, 2020) is about 232 000 ventilator days, with a peak shortfall of 17 200 ventilators on April 19, 2020. Results are also reported for a worst-case where the demand is at the upper limit of the 95% confidence interval. An important finding of this study is that a central agency (FEMA) can act as a coordinator for sharing critical resources that are in short supply over time to add efficiency in the system. Moreover, through properly managing risk-aversion of different entities (states) additional efficiency can be gained. An additional implication is that ramping up production early in the planning cycle allows to reduce shortfall significantly. An optimal timing of this production ramp-up consideration can be based on a cost-benefit analysis.     

基于资源平衡的分布式星群网络连接接入策略

针对现有卫星网络接入策略未能充分考虑卫星资源以及合理确定卫星资源权重问题,提出了一种基于资源平衡的星群网络连接接入策略。该策略充分考虑卫星的多种资源建立卫星资源评价模型,利用移动代理技术,采用层次分析法和熵值法计算各卫星资源的主观和客观权重,并通过Kullback散度权重优化方法对主客观权重进行平衡处理,判决过程兼顾了卫星的综合性能水平和用户偏好,提高了接入的准确性和合理性。仿真结果表明,采用该接入策略,有效改善了新呼叫阻塞率和强制中断率。     

改进柔性资源约束项目调度模型与粒子群算法

在资源受限项目调度问题中,将可再生资源进一步拓展为具有能力差异的柔性资源,建立考虑能力差异的柔性资源受限的多模式项目调度问题模型,该模型是对传统资源约束项目调度问题(RCPSP)更接近实际的拓展。提出了基于粒子群算法的求解算法,粒子群算法求解该模型的思路为,利用蒙特卡洛方法根据资源-能力矩阵与活动模式-能力矩阵得到活动模式-资源矩阵,将考虑能力差异的柔性资源受限的多模式项目调度问题转换为常规的多模式项目调度问题,然后利用基于任务序列与模式表示的粒子群算法对该多模式项目调度问题进行求解。用数值实例说明了模型的合理性与算法的有效性。     

一种基于目标的雷达对抗侦察策略

传统的电子战接收系统的搜索方式主要针对参数完全未知的敌方信号,通过在频域、空域等各维度进行大范围的逐段重复搜索可在较长时间内获得较好的侦察效果,但不适合短时间内对特定目标群的搜索和验证。针对电子战接收机存在的盲目侦察接收、与作战目标结合不紧密等问题,提出了一种基于作战目标的侦察策略,能够智能引导超外差接收机进行搜索截获,有效提升了超外差接收机对重点目标的实时截获与准确识别能力。     

改进蚁群算法在P2P网络资源搜索中的应用

针对P2P网络搜索算法中冗余查询消息过多,资源搜索效率低的问题,提出了基于改进蚁群算法的P2P资源搜索算法,算法中在选择邻节点查询时,综合考虑到本地资源情况、邻节点资源情况、邻节点资源相似度等因素,尽量避开了资源搜索中的恶意节点,并改进了基本蚁群算法的状态转移规则,从而避免了查询消息的盲目发送。仿真实验表明,与传统资源搜索算法K-radom-walks和Flooding相比,该算法在搜索命中率和带宽利用率方面有明显提高。     

云平台上基于关键路径截取的有向无环图应用调度算法

针对云平台上有向无环图科学应用执行容易产生虚拟机资源过剩、资源使用率低及费用虚高的问题,给出一种基于关键路径截取的有向无环图应用调度算法。该算法采取关键路径截取技术,循环找出最晚完成的未分配任务,从该任务出发,在所有未分配任务构成的图中找出最大连通子图,并计算该子图的关键路径,然后将关键路径上的任务集调度到性能匹配的虚拟机上执行;同时通过任务回填技术充分利用虚拟机的空闲时间槽,提高资源使用率。实验结果表明,在云计算平台上,该算法不仅能够在截止时间内完成有向无环图科学应用,而且可以提高资源使用率,有效减少完成该应用所需整体费用。     

Neglected but affected: voices from the oil-producing regions of Ghana and Uganda

The ‘resource curse’ is the paradoxical theory frequently used to explain how a seemingly desirable asset, such as oil, can actually pervert an economy, erode governance, perpetuate conflict, and ruin local communities to the extent that it becomes a curse. New oil discoveries in western Ghana and western Uganda have raised concerns for the democratic prospects and future stability of these countries and their surrounding regions. Based on field interviews in these oil-producing regions, this report summarises how local communities have been affected thus far and their concerns for the future. The authors assess the extent to which each country is vulnerable to oil-induced instability, and identify groups or communities that would be most likely to perpetuate it. Lastly, it provides some assessment of the future trajectory of each country.     

THE SUPPLY PRICE OF COMMITMENT: EVIDENCE FROM THE AIR FORCE ENLISTMENT BONUS PROGRAM

In fiscal year 1999, the US Air Force introduced a bonus program designed to encourage longer enlistment terms. This regime shift provides a unique opportunity to estimate the elasticity of labor supply at a new margin: the length of the employment contract. A $5000 bonus differential is estimated to increase the probability that a recruit will choose a 6‐year enlistment over a 4‐year enlistment by 30 percentage points. The program is found to be cost‐effective relative to other policies to increase man‐years.     

装备保障资源确定技术研究与需求分析系统开发

维修资源是实施装备维修工作的物质基础和重要保证,无论是平时训练还是战时抢修,维修资源都占据着十分重要的地位,不仅影响着装备的寿命周期费用(Life Cycle Costs,LCC),还直接影响着装备的战备完好率以及部队战斗力的保持和恢复.应用更加科学高效的方法确定保障资源,是维修决策面临的重要问题之一.据此,着眼于部队装备维修保障现状需求,将维修任务分配与保障资源需求紧密结合,提出了保障资源确定分析流程,并对分析过程中的关键技术进行了相应的研究,建立了典型的维修决策模型,优化了保障资源配置.最后开发了计算机辅助决策分析系统,为维修资源的优化配置起到了很好的辅助决策作用.