基于粒子群优化算法的空中目标定位

受干扰条件下,雷达难以对空中目标准确定位。针对这一问题,提出了当多基雷达接收站在空间随机分布时,利用粒子群优化算法解决根据到达时间差对空中目标定位中遇到的非线性最优化问题。所建算法首先初始化一个随机粒子群,然后根据适应度值更新粒子速度和位置,通过迭代搜索最佳坐标。仿真结果表明,在参数设定合理的情况下,该算法性能稳定,能找到逼近全局最优点的解。     

弹炮结合武器系统火力分配优化问题研究

在确定弹炮结合武器系统对目标的可射击系数、火力重叠修正系数和转火矛盾修正系数的基础上,结合防空作战的实际,通过对运用地空导弹射击、运用高炮射击、运用地空导弹和高炮混合射击三种情况的分析,介绍了解决弹炮结合武器系统火力分配优化问题的一般步骤。通过算例,证明了该方法的可行性,为有效解决弹炮结合武器系统火力分配优化问题提供了一种较为科学的方法。     

常规导弹战前运输任务优化模型

制定常规导弹战前运输计划时,各车辆运输时间和运输路线的安排是一个组合优化问题.运用军事运筹学和不确定性优化理论,充分考虑节点冲突性、车辆隐蔽性、任务时间、道路容量等因素,建立了运输任务方案的优化模型.该研究为常规导弹波次作战计划的制定和优化提供模型支持,有助于提高常规导弹作战指挥自动化和部队的生存能力.     

基于数值模拟的拔伸成形工艺分析与优化

变薄拔伸是厚壁深筒件生产的关键工序,成形难度大.针对现行的拔伸成形工艺,为改善成形稳定性、提高成形质量、延长模具寿命,通过采用刚粘塑性有限元法,根据不同参数和条件,在计算机上对拔伸工艺进行数值模拟分析,分别讨论了拔伸模圈道数、变形量分配、模圈间距及入模角等因素对拔伸成形过程的影响,进而提出了"多模短距长拔"、变形量依次递减和较小入模角等优化措施.这样既减少了大量现场试验,又达到了工艺优化的目的.     

基于约束满足的多目标对地观测卫星成像调度

EOS(对地观测卫星)成像调度需要根据用户提出的成像任务需求确定卫星成像序列,是一个复杂的组合优化问题。考虑到成像侧视约束条件,建立EOS成像调度的多目标有向无环约束图模型。在此模型的基础上提出了基于SPEA2(strength pareto evolutionary algorithm 2)的多目标成像调度算法,采用约束控制技术设计遗传算子处理成像约束。经过三个实际的多目标成像调度问题测试,表明该算法可以有效地解决EOS成像调度问题。     

超燃冲压发动机燃烧室构型优化的试验研究

在直连式超燃冲压发动机试验系统上,通过调节超燃冲压发动机燃烧室壁面扩张角和燃料喷注位置,对燃烧室构型优化进行了试验研究。为了提高试验效率,燃烧室形面调节采用正交试验设计方法进行组织,每个形面进行5种喷注位置的试验,每次试验通过文氏管调节3个当量比的燃料流量。利用试验数据构造燃烧室性能关于构型参数的响应面模型,可用于燃烧室构型优化。通过两次渐进优化获得了性能更优的燃烧室构型,并根据试验数据分析了各构型参数对燃烧室性能的影响,结果表明:优化构型燃烧室的推力增益比基准构型增大了10.4%;燃烧室性能受各构型参数的强烈耦合影响。     

A novel modeling approach for express package carrier planning

Express package carrier networks have large numbers of heavily‐interconnected and tightly‐constrained resources, making the planning process difficult. A decision made in one area of the network can impact virtually any other area as well. Mathematical programming therefore seems like a logical approach to solving such problems, taking into account all of these interactions. The tight time windows and nonlinear cost functions of these systems, however, often make traditional approaches such as multicommodity flow formulations intractable. This is due to both the large number of constraints and the weakness of the linear programming (LP) relaxations arising in these formulations. To overcome these obstacles, we propose a model in which variables represent combinations of loads and their corresponding routings, rather than assigning individual loads to individual arcs in the network. In doing so, we incorporate much of the problem complexity implicitly within the variable definition, rather than explicitly within the constraints. This approach enables us to linearize the cost structure, strengthen the LP relaxation of the formulation, and drastically reduce the number of constraints. In addition, it greatly facilitates the inclusion of other stages of the (typically decomposed) planning process. We show how the use of templates, in place of traditional delayed column generation, allows us to identify promising candidate variables, ensuring high‐quality solutions in reasonable run times while also enabling the inclusion of additional operational considerations that would be difficult if not impossible to capture in a traditional approach. Computational results are presented using data from a major international package carrier. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Optimal sensor placement for underwater threat detection

The optimization framework for optimal sensor placement for underwater threat detection has been developed. It considers single‐period and multiperiod detection models, each of which includes two components: detection algorithm and optimization problem for sensor placement. The detection algorithms for single‐period and multiperiod models are based on likelihood ratio and sequential testing, respectively. For the both models, the optimization problems use the principle of superadditive coverage, which is closely related to energy‐based and information‐based approaches. An algorithm for quasi‐regular sensor placement approximating solutions to the optimization problems has been developed based on corresponding continuous relaxations and a criterion for its applicability has been obtained. Numerical experiments have demonstrated that the algorithm consistently outperforms existing optimization techniques for optimal sensor placement.© 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

灰色局势决策理论在炮兵火力计划优选中的运用

为了解决炮兵火力计划选择的随意性和盲目性,提出了以灰色理论为基础,综合考虑炮兵火力计划的性质和拟制原则的优选方法;深入研究了局势决策在计划优选中的应用;最后举例说明了灰色局势决策理论在计划优选中的应用,进一步证明了其科学性和创新性,为优选决策提供了一种定量和定性相结合的新方法。