具有不完全信息语言多指标电子对抗计划优选方法

针对指标权重信息不完全且指标值为语言评价信息的电子对抗行动计划优选问题,给出了一种新的决策分析方法。首先建立并规范化了电子对抗行动计划的评价指标;其次给出了计划的优选步骤,其核心是通过计算理想点与计划值的距离、建立线性规划模型,确定指标权重;将语言评价信息转化为三角模糊数,相应地建立可能度,进而获得计划的综合评价值。最后通过算例分析说明了该方法的合理性和有效性。     

小生境粒子群支持向量机的网络故障诊断

针对支持向量机(SVM)在网络故障诊断中应用存在的参数设置和诊断模型复杂的问题,提出一种基于小生境粒子群优化的SVM解决方案。算法在进行参数寻优的同时考虑支持向量个数,实现对诊断模型复杂度的优化,并采用小生境粒子群算法进行求解,提高算法跳出局部最优的能力。在DARPA数据集上的实验表明本文提出的方法能够有效提高诊断模型的泛化性和诊断速度。     

战术导弹制导控制系统一体化设计仿真平台

对战术导弹的制导控制系统的设计阶段和特点进行了分析研究,对设计流程及所用到的方法进行了研究,在研究的基础上提出了制导控制系统一体化设计仿真分析平台的思路,该平台可用于常规导弹制导控制系统的一体化设计,包括导弹的控制系统设计分析、制导律设计、制导控制系统的数学建模与仿真、半实物仿真分析以及系统性能评估等,具有可扩展性,为战术导弹制导控制系统研究提供模块化手段,加速战术导弹的研制进度。     

基于跨层协议模型的机间自组织网络优化研究

节点高速移动、拓扑动态变化、传输质量不稳定是机间自组织网络的基本特征,空中环境的特殊性使得网络适应能力和传输效率成为机间自组织网络面临的最基本挑战。分析机间自组织网络的功能需求、传统的分层协议模型在应用过程中存在的问题,提出机间自组织网络跨层协议模型和跨层优化方法,指出研究中面临的难题和技术方向,为机间自组织网络协议设计提供参考。     

基于多群体改进萤火虫算法的装配序列规划

为了解决机械产品装配序列优化问题,提出了一种基于多群体改进萤火虫优化算法的装配序列规划方法。建立了装配序列规划的数学模型,针对萤火虫算法收敛效率低的不足,借鉴混合蛙跳算法族群划分思想对萤火虫算法进行了改进,引用局部搜索与全局信息交换机制提升了算法性能;根据装配序列规划问题离散型的特点,定义了新的离散编码方式和粒子更新策略。通过实例仿真结果表明,改进后的萤火虫优化算法简单有效、稳定性好、求解精度高,能够稳定快速地给出装配序列最优方案。     

Single‐commodity stochastic network design under demand and topological uncertainties with insufficient data

Stochastic network design is fundamental to transportation and logistic problems in practice, yet faces new modeling and computational challenges resulted from heterogeneous sources of uncertainties and their unknown distributions given limited data. In this article, we design arcs in a network to optimize the cost of single‐commodity flows under random demand and arc disruptions. We minimize the network design cost plus cost associated with network performance under uncertainty evaluated by two schemes. The first scheme restricts demand and arc capacities in budgeted uncertainty sets and minimizes the worst‐case cost of supply generation and network flows for any possible realizations. The second scheme generates a finite set of samples from statistical information (e.g., moments) of data and minimizes the expected cost of supplies and flows, for which we bound the worst‐case cost using budgeted uncertainty sets. We develop cutting‐plane algorithms for solving the mixed‐integer nonlinear programming reformulations of the problem under the two schemes. We compare the computational efficacy of different approaches and analyze the results by testing diverse instances of random and real‐world networks. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 154–173, 2017     

Probabilistic analysis of an asymptotically optimal solution for the completion time variance problem

Scheduling a set of n jobs on a single machine so as to minimize the completion time variance is a well‐known NP‐hard problem. In this paper, we propose a sequence, which can be constructed in O(n log n) time, as a solution for the problem. Our primary concern is to establish the asymptotical optimality of the sequence within the framework of probabilistic analysis. Our main result is that, when the processing times are randomly and independently drawn from the same uniform distribution, the sequence is asymptotically optimal in the sense that its relative error converges to zero in probability as n increases. Other theoretical results are also derived, including: (i) When the processing times follow a symmetric structure, the problem has 2^{⌊(n−1)/2⌋} optimal sequences, which include our proposed sequence and other heuristic sequences suggested in the literature; and (ii) when these 2^{⌊(n−1)/2⌋} sequences are used as approximate solutions for a general problem, our proposed sequence yields the best approximation (in an average sense) while another sequence, which is commonly believed to be a good approximation in the literature, is interestingly the worst. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 373–398, 1999     

Minimizing sums and products of linear fractional functions over a polytope

In this paper, we develop efficient deterministic algorithms for globally minimizing the sum and the product of several linear fractional functions over a polytope. We will show that an elaborate implementation of an outer approximation algorithm applied to the master problem generated by a parametric transformation of the objective function serves as an efficient method for calculating global minima of these nonconvex minimization problems if the number of linear fractional terms in the objective function is less than four or five. It will be shown that the Charnes–Cooper transformation plays an essential role in solving these problems. Also a simple bounding technique using linear multiplicative programming techniques has remarkable effects on structured problems. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 583–596, 1999     

卫星导航抗干扰接收机信道大动态范围通用设计方法研究*

为适应“导航战”下的强干扰输入,导航接收机对模拟信道的动态范围提出了更高的要求。在给定的信噪比恶化容限约束下,原有的分析方法给出了二维曲线分析模型,得到了动态范围的优化设计及各级增益划分方法,但仅适用于输出功率基本不变的AGC电路。基于增加的AGC输出回退功率这一参数,论文提出了一种三维曲面求解模型,揭示了各电路参量与模拟信道动态范围的约束关系,可适用于输出功率变化的AGC电路,以实现更高的动态范围。针对三维模型中参数求解复杂的问题,利用纯衰减网络的特性将复杂的数值求解简化为直线求解,大幅降低了设计复杂度。在给出的设计实例中,动态范围测试结果与设计预期吻合较好,验证了方法的正确性。     

串联式反后坐装置设计与动力学仿真

利用Runge-Kutta方法确定了火炮串联式后坐系统的参数,设计出串联式反后坐装置结构,并运用ADAMS软件进行了串联式后坐系统动力学仿真,以验证设计结果的准确性。动力学仿真结果与结构设计的参数比较吻合,证明了结构设计结果的准确性,通过串联式后坐系统与单一后坐系统的对比,反映了串联式后坐系统的优越性。