Analytic solution for the nucleolus of a three‐player cooperative game

The nucleolus solution for cooperative games in characteristic function form is usually computed numerically by solving a sequence of linear programing (LP) problems, or by solving a single, but very large‐scale, LP problem. This article proposes an algebraic method to compute the nucleolus solution analytically (i.e., in closed‐form) for a three‐player cooperative game in characteristic function form. We first consider cooperative games with empty core and derive a formula to compute the nucleolus solution. Next, we examine cooperative games with nonempty core and calculate the nucleolus solution analytically for five possible cases arising from the relationship among the value functions of different coalitions. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Optimal service and arrival rates in Jackson queueing networks

In this paper we present an algorithm for solving a class of queueing network design problems. Specifically, we focus on determining both service and arrival rates in an open Jackson network of queueing stations. This class of problems has been widely studied and used in a variety of applications, but not well solved due to the difficulty of the resulting optimization problems. As an example, consider the classic application in computer network design which involves determining the minimum cost line capacities and flow assignments while satisfying a queueing performance measure such as an upper limit on transmission delay. Other application areas requiring the selection of both service and arrival rates in a network of queues include the design of communication, manufacturing, and health care systems. These applications yield optimization problems that are difficult to solve because typically they are nonconvex, which means they may have many locally optimal solutions that are not necessarily globally optimal. Therefore, to obtain a globally optimal solution, we develop an efficient branch and bound algorithm that takes advantage of the problem structure. Computational testing on randomly generated problems and actual problems from a health care organization indicate that the algorithm is able to solve realistic sized problems in reasonable computing time on a laptop computer. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 1–17, 2000     

An optimal recursive method for various inventory replenishment models with increasing demand and shortages

We establish various inventory replenishment policies to solve the problem of determining the timing and number of replenishments. We then analytically compare various models, and identify the best alternative among them based on minimizing total relevant costs. Furthermore, we propose a simple and computationally efficient optimal method in a recursive fashion, and provide two examples for illustration. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 791–806, 1997     

基于时滞分割法的具有leakage项时滞的离散型神经网络状态估计

摘要：研究一类具有leakage时滞的离散型神经网络的状态估计问题．通过构造新的Lyapunov泛函得到保证估计误差全局渐近稳定的充分条件,并通过求解一个线性矩阵不等式（LMI）得到状态估计器的增益矩阵．采用一种新的时滞分割方法将变时滞区间分割为多个子区间,使该结果在获得更小的保守性同时也降低了计算的复杂度．     

重型鱼雷的机动搜索及机动搜索弹道架构

针对潜射重型鱼雷在技术性能上的大幅提高和智能化作战的需要,在提出并分析鱼雷机动搜索概念和机动搜索时机的基础上,研究了远程重型鱼雷实现机动搜索在弥补发射平台目标定位误差、鱼雷发射后目标的有意机动和适应点对域攻击战法转变等作战环节中的必要性,构建了重型鱼雷机动搜索弹道的技术框架.     

基于方位量测的舰艇对潜定位技术研究*

结合舰艇拖曳线列阵声纳实际搜潜装备,利用舰载线列阵声纳测得的潜艇目标方位信息,建立了基于方位量测的舰艇对潜艇目标定位的数学模型,给出求解潜艇运动参数的定位算法,并对定位误差进行了分析,在定位模型及算法的基础上,仿真研究了潜艇与舰艇之间的初始距离、舰艇测得潜艇目标初始方位角、潜艇航向等因素对定位性能的影响,给出仿真结果并进行了分析,该结果对于指导实际反潜具有一定的实用价值.     

利用混合编程改善SMP机群上并行矩阵乘法的性能

针对SMP机群,探讨了分别利用单机优化、OpenMP与MPI从指令级、共享存储级与分布主存级三个层次上改善矩阵并行乘Fox算法性能的方法。并通过调用数学函数库与混合编程的方式,在深腾6800上进行了实验,取得了相当满意的数值效果。     

基于运动合成的小推力轨道优化方法

针对小推力轨道优化设计问题,提出一种基于运动合成的新方法。给出基于运动合成的小推力轨道机动表达方式,将小推力轨道运动分解成相对独立的三项:单独考虑日心引力的二体轨道运动,单独考虑小推力的运动,以及小推力的存在引起的日心引力摄动作用下的运动。分别给出各项运动的解析表达式,通过合成叠加得到小推力轨道的近似解析解。在此基础上,将小推力轨道优化问题转化成非线性规划问题,并利用序列二次规划方法求解。以小行星1989ML、火星和金星交会任务为例分别进行仿真实验,结果表明,所设计轨道满足任务约束,验证了该方法具有可用性和高效性。     

区域防空导弹反导火力分配研究

分析了传统防空导弹火力分配模型的不足,考虑到编队内各舰艇近程防空作战能力的不同,结合装备性能特点,建立了基于机会约束规划的区域防空导弹火力分配优化模型。给出了基于遗传算法和BP神经网络的混合智能算法,该算法在精度和速度上均能满足防空作战的要求。     

Cρ 准则下选择最优子集的并行算法

C_p准则是目前颇受重视的一种变量选择准则。本文针对大型线性回归模型,推导了从所有可能子集中用C_p准则选择最优子集的(乘除法) 运算次数,提出了C_p准则下变量选择的并行算法。给出了在YH-1和YH-2向量巨型计算机上运行该算法的模拟结果且获得了15倍左右的向量加速比s/v,体现了该算法的优越性。