相依目标群系统火力分配问题分析与解法

本文中讨论由若干个相依目标群组成的平面点目标系统的火力分配问题。对于武器型号相同的情形,得到了“边际毁伤递减原理”和“循序最优方案即全局最优方案”等结论,并在此基础上提出了问题的解算方法。对于武器型号不同的情形,提出了“循序最优枚举法”,并得出有关结论。     

多机环境下多帧速系统仿真的若干问题

本文论述了多帧速系统在多机环境下并行仿真时处理机分配的原则,指出为减少通信开销,应将多帧速系统中各个子系统分配到不同的处理机(群) 上并行处理。并给出了多帧速系统的仿真主控流程。     

随机通信网络分时管理分析

分析了时分网络的主要性能指标─—信息传递准确率,并给出了其在各种节点类型中的计算公式,据此总结了时分网络中时隙分配的一些原则。     

Allocation with demand competition: Uniform,proportional, and lexicographic mechanisms

We examine capacity allocation mechanisms in a supply chain comprising a monopolistic supplier and two competing retailers with asymmetric market powers. The supplier allocates limited capacity to retailers according to uniform, proportional, or lexicographic mechanism. We study the impact of these allocation mechanisms on supplier pricing decisions and retailer ordering behavior. With individual order size no greater than supplier capacity, we show that all three mechanisms guarantee equilibrium ordering. We provide precise structures of retailer ordering decisions in Nash and dominant equilibria. Further, we compare the mechanisms from the perspective of the supplier, the retailers, and the supply chain. We show that regardless of whether retailer market powers are symmetric, lexicographic allocation with any priority sequence of retailers is better than the other two mechanisms for the supplier. Further, under lexicographic allocation, the supplier gains more profit by granting higher priority to the retailer with greater market power. We also extend our study to the case with multiple retailers. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 85–107, 2017     

多机协同目标与火力资源分配

在协同空战中,快速正确的空战决策是己方战机少受敌方伤害并取得战争胜利的前提。目标与火力资源分配是决策过程的重要部分。多机空战与单机空战相比有明显的不同,不同之处是面临多个敌方目标,根据我方资源最优分配作战对象和火力,基于遗传算法实现了两种算法的有人无人目标与火力资源分配。仿真结果表明,带有毁伤概率门限的算法既节省火力资源又快速有效。     

战场信息资源共享平台

针对现行指挥自动化系统在战场信息广泛共享上的差距,构建战场信息共享平台(PW IRS:P latform on W ar-F ie ld In form ation R esources Sharing)模型,提出了战场信息共享平台的体系结构,并在上述的基础上,实现了战场信息资源共享平台的实验原型。     

Discrete equal‐capacity p‐median problem

This paper examines the discrete equal‐capacity p‐median problem that seeks to locate p new facilities (medians) on a network, each having a given uniform capacity, in order to minimize the sum of distribution costs while satisfying the demand on the network. Such problems arise, for example, in local access and transport area telecommunication network design problems where any number of a set of p facility units can be constructed at the specified candidate sites (hence, the net capacity is an integer multiple of a given unit capacity). We develop various valid inequalities, a separation routine for generating cutting planes that are specific members of such inequalities, as well as an enhanced reformulation that constructs a partial convex hull representation that subsumes an entire class of valid inequalities via its linear programming relaxation. We also propose suitable heuristic schemes for this problem, based on sequentially rounding the continuous relaxation solutions obtained for the various equivalent formulations of the problem. Extensive computational results are provided to demonstrate the effectiveness of the proposed valid inequalities, enhanced formulations, and heuristic schemes. The results indicate that the proposed schemes for tightening the underlying relaxations play a significant role in enhancing the performance of both exact and heuristic solution methods for this class of problems. © 2000 John & Sons, Inc. Naval Research Logistics 47: 166–183, 2000.     

基于网格的资源目录管理的设计与管理

资源目录管理是网格系统软件的重要组成部分。通过实例研究基于网格的资源目录管理的设计与实现。资源目标管理的设计基于LDAP协议 ,直接采纳了LDAP的标准数据表示和数据存储方法 ,并结合网格系统的自身特点设计网格中的信息表示方法和数据模型。资源目录管理的实现采用目录管理软件Openldap1 2 7和后台数据gdbm1 8 0 ,对其中的关键技术和主要步骤都做了重点研究并举例说明     

无标度网络上的队列资源重分配策略

在实际的通信系统中,由于物理条件的限制,每个节点都具有有限长度的队列。研究了在有限队列资源的条件下,队列资源对无标度数据流动力学的影响。提出了一种队列资源重分配策略,策略中节点的队列长度与节点的介数成正比。仿真结果表明,在无标度网络中使用最短路径路由的条件下,所提出的重分配策略可以有效地改进网络的容量。同时对有限队列资源条件下的网络容量进行了理论分析。     

Two-agent scheduling with linear resource-dependent processing times

This paper considers a two-agent scheduling problem with linear resource-dependent processing times, in which each agent has a set of jobs that compete with that of the other agent for the use of a common processing machine, and each agent aims to minimize the weighted number of its tardy jobs. To meet the due date requirements of the jobs of the two agents, additional amounts of a common resource, which may be in discrete or continuous quantities, can be allocated to the processing of the jobs to compress their processing durations. The actual processing time of a job is a linear function of the amount of the resource allocated to it. The objective is to determine the optimal job sequence and resource allocation strategy so as to minimize the weighted number of tardy jobs of one agent, while keeping the weighted number of tardy jobs of the other agent, and the total resource consumption cost within their respective predetermined limits. It is shown that the problem is -hard in the ordinary sense, and there does not exist a polynomial-time approximation algorithm with performance ratio unless ; however it admits a relaxed fully polynomial time approximation scheme. A proximal bundle algorithm based on Lagrangian relaxation is also presented to solve the problem approximately. To speed up convergence and produce sharp bounds, enhancement strategies including the design of a Tabu search algorithm and integration of a Lagrangian recovery heuristic into the algorithm are devised. Extensive numerical studies are conducted to assess the effectiveness and efficiency of the proposed algorithms.