基于稀疏子空间聚类的人脸识别方法

在现有的稀疏子空间聚类算法理论基础上给出两种稀疏子空间聚类优化算法:稀疏线性子空间聚类和稀疏仿射子空间聚类。这两种优化算法针对不同的数据集会有不同的聚类效果。通过稀疏表达得到不同的稀疏系数矩阵,把稀疏系数矩阵应用到较为简单的改进的正则化谱聚类算法中实现聚类。应用Yale B数据对人脸图像进行识别分类得出:采用稀疏线性子空间聚类算法优于稀疏仿射子空间聚类算法;在算法执行时间上和算法聚类错误率比传统的稀疏子空间聚类较为快速高效。     

Balancing perfectly periodic service schedules: An application from recycling and waste management

A national recycling and waste management company provides periodic services to its customers from over 160 service centers. The services are performed periodically in units of weeks over a planning horizon. The number of truck‐hours allocated to this effort is determined by the maximum weekly workload during the planning horizon. Therefore, minimizing the maximum weekly workload results in minimum operating expenses. The perfectly periodic service scheduling (PPSS) problem is defined based on the practices of the company. It is shown that the PPSS problem is strongly NP‐hard. Attempts to solve large instances by using an integer programming formulation are unsuccessful. Therefore, greedy BestFit heuristics with three different sorting schemes are designed and tested for six real‐world PPSS instances and 80 randomly generated data files. The heuristics provide effective solutions that are within 2% of optimality on average. When the best found BestFit schedules are compared with the existing schedules, it is shown that operational costs are reduced by 18% on average. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 59: 160–171, 2012     

战术移动Ad Hoc网络下的分布式位置辅助功率控制算法

针对战术移动自组(AdHoc)网络提出一种分布式位置辅助的功率控制算法(LAPCA),它通过位置预测来推算节点的邻节点数目,进而调整信号发射功率,以保持最佳的网络连通性,由此提高整个网络的有效流量。该算法作为一个独立模块可以方便地与已有的移动自组网络路由协议相结合。采用较为适合战术环境的参考点群组移动(RPGM)模型来产生网络仿真场景,从仿真实验结果来看,几乎在所有的RPGM场景下采用该算法后的网络有效流量相对于纯粹的AODV路由协议都得到了提高。     

Basic scheduling problems with raw material constraints

One of the achievements of scheduling theory is its contribution to practical applications in industrial settings. In particular, taking finiteness of the available production capacity explicitly into account, has been a major improvement of standard practice. Availability of raw materials, however, which is another important constraint in practice, has been largely disregarded in scheduling theory. This paper considers basic models for scheduling problems in contemporary manufacturing settings where raw material availability is of critical importance. We explore single scheduling machine problems, mostly with unit or all equal processing times, and L_max and C_max objectives. We present polynomial time algorithms, complexity and approximation results, and computational experiments. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

超燃冲压发动机二维进气道多级多目标优化设计方法

提出了超燃冲压发动机二维进气道的多级多目标设计方法。选择总压恢复系数、压升比和阻力系数为性能目标,引入多级设计概念,分别基于一维气动力学分析方法和计算流体力学方法,采用混合遗传算法对4楔角外压和2楔角内压混合压缩进气道进行了多级多目标优化设计,得到了问题的Pareto非劣解集。采用上述方法可以提升超燃冲压发动机进气道的设计水平,得到高性能的设计方案。     

程序进化器

研究用模拟进化方法进行程序设计的途径。构造了以形式文法为遗传表示的程序进化器,提出了这个进化器使用的有关算法。本文用程序进化器解决了人工蚁问题。     

基于卫星云图历史资料反演云团非线性预测模型

针对线性预测方法难以有效描述云团的非线性、非平稳变化的困难,基于经验正交函数分解(EOF)和遗传算法参数优化结合的思想,提出了一条云团非线性预测模型反演的方法途径。首先将卫星云图序列作EOF的时、空分解;在此基础上,引入遗传算法对EOF的时间系数序列进行了动力模型重构和模型参数反演,建立了EOF时间系数的非线性微分方程组;再通过时、空函数合成,构造了云团演变的动力预报模型。试验结果表明,反演的云团预报模型能较为合理地描述特定季节区域内云团演变的基本趋势,预测结果与实际云图的主要特征基本相符,尤其是实现了云图3h以上的中、长时效的客观预测。     

On online bin packing with LIB constraints

In many applications of packing, the location of small items below large items, inside the packed boxes, is forbidden. We consider a variant of the classic online one‐dimensional bin packing, in which items allocated to each bin are packed there in the order of arrival, satisfying the condition above. This variant is called online bin packing problem with LIB (larger item in the bottom) constraints. We give an improved analysis of First Fit showing that its competitive ratio is at most , and design a lower bound of 2 on the competitive ratio of any online algorithm. In addition, we study the competitive ratio of First Fit as a function of an upper bound (where d is a positive integer) on the item sizes. Our upper bound on the competitive ratio of First Fit tends to 2 as d grows, whereas the lower bound of two holds for any value of d. Finally, we consider several natural and well known algorithms, namely, Best Fit, Worst Fit, Almost Worst Fit, and Harmonic, and show that none of them has a finite competitive ratio for the problem. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

基于蚁群算法的被动目标定位算法

通过对蚁群算法的研究,用蚁群算法成功解决了无源测向定位中消除虚假点,对真实交点进行正确聚类的难题.并通过Matlab 仿真实验证明了该算法的有效性.同时该算法具有目标关联确率高、计算速度快、鲁棒性强等优点.