基于遗传算法的整周模糊度OTF解算

建立了一种基于简单遗传算法的改进模糊度搜索方法。首先采用一组约束方程求解模糊度浮点数解 ,然后UDUT 和LDLT 分解对整周模糊度进行整数高斯变换以降低各整周模糊度之间的相关性 ,最后利用遗传算法进行整周模糊度搜索。在种群个体较少的情况下 ,为了避免早熟使搜索陷入局部最优 ,提出两种变异算子 ,保持个体的多样性。仿真结果表明改进后的算法能够实时动态解算整周模糊度 ,且较使用简单遗传算法具有更快的搜索速度和鲁棒性。     

基于遗传算法的通信网络可靠性优化设计

在可靠性条件约束下 ,使网络成本最低是网络规划NP hard问题 .文章提出一种基于遗传算法的优化方法解决了这类问题 .仿真结果表明这种算法是有效的 .     

单静止站纯方位系统的可观测性与目标参数估计算法

分析了目标参数Vmx/Do,Vmy/Do 可观测的条件 ,给出了估计这对参数的一种递推算法 .     

A comparative study of three tool replacement/operation sequencing strategies in a flexible manufacturing system

This paper studies three tool replacement/operation sequencing strategies for a flexible manufacturing system over a finite time horizon: (1) failure replacement—replace the tool only upon failure, (2) optimal preventive tool replacement for a fixed sequence of operations, and (3) joint scheduling of the optimal preventive tool replacement times and the optimal sequence of operations. Stochastic dynamic decision models are used for strategies 2 and 3. The optimization criterion for strategies 2 and 3 is the minimization of the total expected cost over the finite time horizon. We will show through numerical studies that, with the same amount of information, the total expected costs can be reduced considerably by choosing an optimal strategy. Our conclusion is that in flexible manufacturing, optimal tool replacement and optimal operations sequencing are not separate issues. They should be considered jointly to minimize the expected total cost. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 479–499, 2000     

Distribution free bounds for service constrained (Q,r) inventory systems

A classical and important problem in stochastic inventory theory is to determine the order quantity (Q) and the reorder level (r) to minimize inventory holding and backorder costs subject to a service constraint that the fill rate, i.e., the fraction of demand satisfied by inventory in stock, is at least equal to a desired value. This problem is often hard to solve because the fill rate constraint is not convex in (Q, r) unless additional assumptions are made about the distribution of demand during the lead‐time. As a consequence, there are no known algorithms, other than exhaustive search, that are available for solving this problem in its full generality. Our paper derives the first known bounds to the fill‐rate constrained (Q, r) inventory problem. We derive upper and lower bounds for the optimal values of the order quantity and the reorder level for this problem that are independent of the distribution of demand during the lead time and its variance. We show that the classical economic order quantity is a lower bound on the optimal ordering quantity. We present an efficient solution procedure that exploits these bounds and has a guaranteed bound on the error. When the Lagrangian of the fill rate constraint is convex or when the fill rate constraint does not exist, our bounds can be used to enhance the efficiency of existing algorithms. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 635–656, 2000     

具有节点失效的网络可靠度的信息交互算法

提出了一种用于计算具有节点失效的网络可靠度的新计算方法。该算法依据不交化代数及协同计算的思想,采用节点信息义互的方法直接获得网络的不交化最小路集。算法简便易行,具有分布计算的特点,为大型网络系统的可靠性度计算提供了一种新的途径。     

变分自编码器结合聚类算法在空战态势评估问题上的应用

针对传统态势评估方法确定权值的主观性强、处理大数据能力弱、特征提取能力不足等问题,提出基于改进变分自编码器和聚类算法的无监督空战态势评估方法。根据态势变化连续性特点,提出基于时间段的空战态势分类方法,将敌我双方态势划分为四类。在变分自编码器的基础上,提出了VAE-WRBM-MDN特征提取模型,即使用混合密度网络优化变分自编码器的特征提取能力和生成数据的相似度,使用权值不确定限制玻尔兹曼机优化网络的初始权值。将提取的特征分别输入到两种典型的聚类算法中进行聚类,并结合态势函数和实际战场情况修正聚类结果,形成正确的态势分类标准。在实验部分,分别进行了最优参数调整、关键特征提取、聚类以及修正实验。实验结果表明,模型态势分类正确率和运行时间均满足应用需求,实例评估结果与客观态势一致性强,所提方法具有实际应用价值。     

Mathematical formulation and heuristic algorithm for the block relocation and loading problem

This study considers the block relocation and loading problem in container terminals. The optimal loading sequence and relocation location are simultaneously decided on the basis of the desired ship‐bay and initial yard space configuration. An integer linear programming model is developed to minimize the number of relocations in the yard space on the basis of no shifts in the ship bay. The accuracy of the model is tested on small‐scale scenarios by using CPLEX. Considering the problem size in the real world, we present a rule‐based heuristic method that is combined with a mathematical model for the removal, loading, and relocation operations. The influence of rules on algorithm performance is also analyzed, and the heuristic algorithm is compared with different types of algorithms in the literature. The extensive numerical experiments show the efficiency of the proposed heuristic algorithm.     

改进遗传算法在传声器阵列优化中的应用

规则平面阵列因其结构周期性,在进行波束综合时存在主瓣宽、旁瓣电平高等问题。对此,提出一种基于改进遗传算法的阵列优化方法。设计平面栅格传声器阵列,以满足阵元间距的要求,并构造以主瓣宽度为约束条件、以全局旁瓣电平为适应度的目标函数,对常规遗传算法进行改进,采取个体间自由交叉、随机的阵元数量强制变异的策略来增大种群的搜索范围。通过仿真,得到多个优化阵列,与几种规则平面阵列相比,在不同的信噪比输入下,经过改进遗传算法优化得到的随机阵列均有更好的表现。而相比于几种常规的优化算法,改进的遗传算法具有更强的搜索能力,得到数量更多、性能更优的随机阵列,由此证明了所提方法的可行性。     

基于Floyd算法的常规导弹连续波次作战运输规划

为提高常规导弹连续波次作战效能,对常规导弹连续波次作战运输规划问题进行研究。以Floyd算法为基础,首先生成了作战机动区域的交通网络最短路径、距离矩阵;其次将常规导弹连续波次作战运输过程分解为不同阶段,以运输过程中的整体暴露时间最短为目标,构建了初始规划方案0-1整数规划模型;然后考虑道路通行量及地域容量限制,对初始规划方案中存在的地域容量超过限制及单行道路中会车、超车情况进行逐步循环优化,以得到最佳运输规划方案;最后选择了一个作战案例想定,通过Matlab编程对案例进行了求解,得到了针对此案例的最佳运输规划方案,验证了模型的正确性和算法的有效性。