多边形障碍环境中避障路径的遗传算法

研究了平面障碍环境中避障的遗传算法,重点介绍了障碍环境的模型构造和用遗传算法求解该模型的方法设计.采用了与已有遗传算法不同的染色体编码方式和不同的遗传算子设计,在初始群体产生时尽量避免了引入无效基因,提高了染色体进化的效率,使得该算法具有很好的寻优能力,实验结果也表明了该算法的有效性.     

The bottleneck problem with minimum quantity commitments

Given an edge‐distance graph of a set of suppliers and clients, the bottleneck problem is to assign each client to a selected supplier minimizing their maximum distance. We introduce minimum quantity commitments to balance workloads of suppliers, provide the best possible approximation algorithm, and study its generalizations and specializations. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

A misclassification cost‐minimizing evolutionary–neural classification approach

Machine learning algorithms that incorporate misclassification costs have recently received considerable attention. In this paper, we use the principles of evolution to develop and test an evolutionary/genetic algorithm (GA)‐based neural approach that incorporates asymmetric Type I and Type II error costs. Using simulated, real‐world medical and financial data sets, we compare the results of the proposed approach with other statistical, mathematical, and machine learning approaches, which include statistical linear discriminant analysis, back‐propagation artificial neural network, integrated cost preference‐based linear mathematical programming‐based minimize squared deviations, linear integrated cost preference‐based GA, decision trees (C 5.0, and CART), and inexpensive classification with expensive tests algorithm. Our results indicate that the proposed approach incorporating asymmetric error costs results in equal or lower holdout sample misclassification cost when compared with the other statistical, mathematical, and machine learning misclassification cost‐minimizing approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

X波段矩形波导宽边复合缝隙耦合器的MPSTD算法分析

针对MPSTD算法在波导宽边复合缝隙问题中的应用,重点研究了X波段标准波导宽边复合缝隙耦合器的缝隙谐振长度和散射参量特性。仿真结果表明,将MPSTD算法应用于波导耦合缝隙问题的分析,可实现对该问题的精确建模,具有较高的计算精度和效率。     

矩阵外积法Kalman滤波器在动态GPS定位中的应用

由于计算机有效字长的限制,滤波算法在计算机上实施时易于产生误差积累,误差协方差失去正定性或对称性,从而出现数值计算中的不稳定现象.一般情况下,当状态变量维数超过10时,滤波过程中出现滤波结果不稳定现象概率增大.为了解决滤波器数值计算不稳定问题,实践中提出并应用了许多方法,如自适应滤波、固定增益滤波、平方根滤波等.这些算法的不足是计算繁琐,效率低下.提出一个基于矩阵外积法所设计的快速、稳定的滤波算法,该卡尔曼滤波算法速度快,效率高,数值稳定性好,运算量少,将其应用于动态GPS定位验证了其有效性.     

An experiment evaluating how the tiny mass eccentricities in spin-stabilized projectiles affect the position of impact points

This study investigates and quantifies some possible sources affecting the position of impact points of small caliber spin-stabilized projectiles (such as 12.7 mm bullets). A comparative experiment utilizing the control variable method was designed to figure out the influence of tiny eccentric centroids on the projectiles. The study critically analyzes data obtained from characteristic parameter measurements and precision trials. It also combines Sobol's algorithm with an artificial intelligence algorithm—Adaptive Neuro-Fuzzy Inference Systems (ANFIS)—in order to conduct global sensitivity analysis and determine which parameters were most influential. The results indicate that the impact points of projectiles with an entry angle of 0° deflected to the left to that of projectiles with an entry angle of 90°. The difference of the mean coordinates of impact points was about 12.61 cm at a target range of 200 m. Variance analysis indicated that the entry angle — i.e. the initial position of mass eccentricity — had a notable influence. After global sensitivity analysis, the significance of the effect of mass eccentricity was confirmed again and the most influential factors were determined to be the axial moment and transverse moment of inertia (Izz Iyy), the mass of a projectile (m), the distance between nose and center of mass along the symmetry axis for a projectile (Lm), and the eccentric distance of the centroid (Lr). The results imply that the control scheme by means of modifying mass center (moving mass or mass eccentricity) is promising for designing small-caliber spin-stabilized projectiles.     

基于改进核极限学习机和集成学习理论的目标机动轨迹预测

为了提高目标轨迹预测的精度以及预测模型的泛化能力,提出基于改进蝙蝠算法优化的核极限学习机(Kernel Extreme Learning Machine,KELM)和集成学习理论目标机动轨迹预测模型。构建KELM模型,并采用改进的蝙蝠算法对KELM的参数进行优化;以优化后的KELM神经网络为弱预测器,结合集成学习算法生成强预测器,通过训练不断优化强预测的结构和参数,得到一种基于集成学习理论的目标机动轨迹预测模型;基于不同规模的样本,将所得预测模型与逆传播神经网络、支持向量机和极限学习机等模型进行对比分析。仿真结果表明:所提目标机动轨迹预测模型具有较好的预测精度和泛化能力。     

一种含最优变异的多微粒群优化算法

针对微粒群优化算法中的固有缺点,提出了带有最优变异算子的多微粒群优化算法,采用多个微粒群对目标函数进行寻优,并在寻优过程中对子群中最优微粒引入了最优变异算子。通过这样的处理,算法可以预防早熟收敛并具有更快的收敛速度和更好的局部开发能力。对一组测试函数的模拟实验结果表明,带最优变异的多微粒群优化算法可以摆脱局部最优解对微粒的吸引,在较少的代数内就能够获得好的优化结果。     

A branch‐and‐price algorithm for a targeting problem

In this paper, we consider a new weapon‐target allocation problem with the objective of minimizing the overall firing cost. The problem is formulated as a nonlinear integer programming model, but it can be transformed into a linear integer programming model. We present a branch‐and‐price algorithm for the problem employing the disaggregated formulation, which has exponentially many columns denoting the feasible allocations of weapon systems to each target. A greedy‐style heuristic is used to get some initial columns to start the column generation. A branching strategy compatible with the pricing problem is also proposed. Computational results using randomly generated data show this approach is promising for the targeting problem. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Integrated capacity,demand, and production planning with subcontracting and overtime options

Models for integrated production and demand planning decisions can serve to improve a producer's ability to effectively match demand requirements with production capabilities. In contexts with price‐sensitive demands, economies of scale in production, and multiple capacity options, such integrated planning problems can quickly become complex. To address these complexities, this paper provides profit‐maximizing production planning models for determining optimal demand and internal production capacity levels under price‐sensitive deterministic demands, with subcontracting and overtime options. The models determine a producer's optimal price, production, inventory, subcontracting, overtime, and internal capacity levels, while accounting for production economies of scale and capacity costs through concave cost functions. We use polyhedral properties and dynamic programming techniques to provide polynomial‐time solution approaches for obtaining an optimal solution for this class of problems when the internal capacity level is time‐invariant. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007