被动传感器融合检测系统的优化分布密度

被动传感器由于采用无源探测,而且制造成本低,体积小,在战场环境中将采用并配置大量的被动传感器来检测目标.不论是主动还是被动式传感器,在实际应用中均存在资源优化配置问题.针对被动传感器的具体应用模型,采取了若干合理近似,得到了在"OR"融合检测条件下,基于最大检测概率的被动传感器优化配置密度计算公式.     

智能理论在BIT设计与故障诊断中的应用

近２０年来机内测试（ＢＩＴ）技术从理论到应用取得了显著进展，已成为提高产品测试性和诊断能力的有效途径。本文概述了ＢＩＴ技术的特点，分析了国内外ＢＩＴ的发展趋势，对ＢＩＴ智能化从系统设计、信息处理到综合决策各阶段进行概括，对专家系统、神经网络、模糊理论、信息融合等智能理论在ＢＩＴ中的应用进行了综合分析，并初步建立智能ＢＩＴ的理论框架     

离散多音调制中一种改进的动态能量分配方法

本文探讨了离散多音调制（ＤＭＴ）中的动态能量分配的特点和应用范围，并分析了几种典型的动态能量分配方法。在此基础上，本文提出了一种改进的分配方法。计算机模拟结果表明，该方法不仅降低了运算复杂度，而且性能近于最优。文章最后还探讨了动态能量分配中尚待进一步解决的问题。     

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。     

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.     

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.