基于遗传算法的军事物流运输计划

针对军事物流运输中车辆装载和车辆路径的组合问题进行研究,建立车辆装载和车辆路径组合问题的目标优化模型。通过改进遗传算法对模型求解,得到了较为满意的结果,可以在满足多车型多品种货物配送约束的条件下,实现运输车辆最少、车辆满载率高、车辆运输路径最短的目标。     

COTS星载计算机容错设计及可靠性研究

为了实现微小卫星“好、快、省”的目标，商业货架产品(Commercial off the shelf, COTS)被大量采用，如何确保COTS产品的可靠性是必须要解决的问题.以基于工业器件的计算机产品为例，针对星载计算机产品存在的空间应用无可靠性预计指标、无抗单粒子设计等问题，开展了星载计算机容错设计及空间应用可靠性研究.为了保证星载计算机高可靠性航天应用，从产品的设计、分析、试验等方面提出了有效的保证措施.最后，利用星载计算机加速寿命试验数据和在轨实际运行表现证明了该方法的有效性；可靠性评估结果表明星载计算机三年内可靠度可以达到0.976以上(置信度取0.6)，能够实现高可靠航天应用.     

基于遗传算法的成人高等教育智能组卷模型的研究与设计

为建立成人高等教育智能组卷模型，利用遗传算法和函数矩阵，对现有组卷系统进行了优化设计，并提出了针对性的改进方案，为成人高等教育的考试组卷提供了适应的技术支持。     

Improved NSGA-II Multi-objective Genetic Algorithm Based on Hybridization-encouraged Mechanism

To improve performances of multi-objective optimization algorithms, such as convergence and diversity, a hybridization- encouraged mechanism is proposed and realized in elitist nondominated sorting genetic algorithm （NSGA-Ⅱ）. This mechanism uses the normalized distance to evaluate the difference among genes in a population. Three possible modes of crossover operators--＂Max Distance＂, ＂Min-Max Distance＂, and ＂Neighboring-Max＂--are suggested and analyzed. The mode of ＂Neighboring-Max＂, which not only takes advantage of hybridization but also improves the distribution of the population near Pareto optimal front, is chosen and used in NSGA-Ⅱ on the basis of hybridization-encouraged mechanism （short for HEM-based NSGA-Ⅱ）. To prove the HEM-based algorithm, several problems are studied by using standard NSGA-Ⅱ and the presented method. Different evaluation criteria are also used to judge these algorithms in terms of distribution of solutions, convergence, diversity, and quality of solutions. The numerical results indicate that the application of hybridization-encouraged mechanism could effectively improve the performances of genetic algorithm. Finally, as an example in engineering practices, the presented method is used to design a longitudinal flight control system, which demonstrates the obtainability of a reasonable and correct Pareto front.     

基于遗传算法的地磁匹配搜索策略

为降低导航成本,提出仅利用磁测计和里程计的地磁场匹配定位方法.为解决搜索空间过大的问题,提出以遗传算法在匹配区域搜索可能路径的方法.该方法以相关性度量作为适应度函数,交叉与变异仅针对点列的相对关系完成,提出用局部适应度函数自适应调整交叉概率与变异概率.仿真结果表明,该方法可以有效完成地磁匹配导航中任意形状路径的匹配.     

基于模糊机会约束规划的机会阵雷达方向图综合

针对机会阵雷达方向图综合的不确定问题,提出了一种基于模糊机会约束规划的方向图综合规划模型。该模型基于可信性理论,综合考虑天线单元分布的随机性以及激励状态的不确定性,将参与方向图综合时激励打开的天线数目看做一个梯形模糊变量,用以描述综合时的复杂不确定环境。随后,将规划模型转化为清晰等价形式,再结合遗传算法和灰关联综合评价法则设计了一种混合智能优化算法,用于求解该模型。以一维任意非均匀线阵为例,对主瓣宽度和最大副瓣电平进行了优化。仿真表明:优化后结果的可信性高于置信水平,验证了该算法的有效性。     

A strategic flight conflict avoidance approach based on a memetic algorithm

Conflict avoidance （CA） plays a crucial role in guaranteeing the airspace safety. The cur- rent approaches, mostly focusing on a short-term situation which eliminates conflicts via local adjust- ment, cannot provide a global solution. Recently, long-term conflict avoidance approaches, which are proposed to provide solutions via strategically planning traffic flow from a global view, have attracted more attentions. With consideration of the situation in China, there are thousands of flights per day and the air route network is large and complex, which makes the long-term problem to be a large-scale combinatorial optimization problem with complex constraints. To minimize the risk of premature convergence being faced by current approaches and obtain higher quality solutions, in this work, we present an effective strategic framework based on a memetic algorithm （MA）, which can markedly improve search capability via a combination of population-based global search and local improve- ments made by individuals. In addition, a specially designed local search operator and an adaptive local search frequency strategy are proposed to improve the solution quality. Furthermore, a fast genetic algorithm （GA） is presented as the global optimization method. Empirical studies using real traffic data of the Chinese air route network and daily flight plans show that our approach outper- formed the existing approaches including the GA .based approach and the cooperative coevolution based approach as well as some well-known memetic algorithm based approaches.     

基于高速慢车的航空发动机快速响应控制

针对传统航空发动机响应速度慢,难以在紧急事件中用于控制受损飞机完成起降过程的问题,采用高速慢车控制模式来提升发动机加速性能,通过增加发动机在慢车时高压压气机转速,为加速前期提供更大的燃油流量,从而缩短发动机从慢车至最大状态的加速时间。为保证慢车时高压转子转速提高的同时发动机推力和稳定裕度不变,通过修改高压压气机可调导叶控制计划来调整高压转子工作点。仿真结果显示,与原有控制相比,采用高速慢车快速响应控制模式的发动机加速上升时间从原来的2.00s缩短至1.86s,而高压压气机最小喘振裕度仅由16.01%下降至14.81%,同时慢车推力基本保持不变。     

基于性能退化模型的空间电子学设备加速寿命试验研究与应用

对基于Arrhenius模型、Norris-Landzberg模型和Peck模型等模型的加速寿命试验理论进行了简要阐述,针对空间应用系统空间电子学设备可靠性特点和加速寿命试验难点,提出了一种基于性能退化模型的电子学整机系统加速应力试验方法,最后给出了实例,为减少试验设计中的不确定性因素提供了一种新的思路。