利用分布式狼群算法进行三维传感器优化布置的方法研究

考虑传感器优化布置中的模态置信准则MAC只能对三维传感器的某一方向进行优化,而不能确保在三个方向同时实现优化布置的问题,提出将节点的三个平动自由度作为一个单元,通过节点的Fisher信息阵来获取结构所布置传感器的Fisher信息阵,并借鉴传统一维模态置信准则的思想,构建了一种全新的三维模态置信准则TMAC。为提高算法的求解效率,提出了一种分布式狼群算法,采用双重编码方式,克服原狼群算法只能求解连续变量优化的问题;采用狼群分组的方法,通过组内狼个体的信息交流,提高了算法的搜索效率。文末以中佛罗里达大学建立的基准模型为例,进行了参数敏感性分析以及三维传感器优化布置方案的选择,结果表明:分布式狼群算法的搜索能力较原狼群算法有了大幅提高,能较好地解决传感器优化布置问题。     

熔融沉积快速成型零件成型方向的多目标优化

为了实现熔融沉积快速成型（FDM）中零件成型精度和成型效率的协同优化,基于零件成型方向对成型精度和成型效率的影响进行分析,以体积误差最小、零件成型方向上高度最低以及所需支撑体积最小为目标,建立了零件成型方向的多目标优化模型。设计了基于非支配排序遗传算法的智能求解算法,通过对模型的优化计算得到零件成型方向的Pareto解集,实现了FDM零件成型方向的智能优化。最后通过实例验证了所建模型的正确性与算法的有效性。     

三维打印快速成型零件制作方向的优化研究

根据光敏树脂材料三维打印快速成型工艺的特点,建立了制件表面质量与零件制作方向之间的优化数学模型.选用搜寻全局最优解能力较强的遗传算法进行最优零件制作方向的求解,实现了三维打印快速成型工艺中零件制作方向的自动优化计算程序.通过试验和测试,该程序可快速求出零件的最优制作方向,提高零件的表面质量.     

数据网格资源选择优化模型

为了满足网格数据服务的可靠性和传输时间约束,同时兼顾网络负载及节点资源的有效利用,提出了一种网格数据资源选择优化模型,该模型以网络负载和资源代价为优化目标函数,以节点的传输速度、可靠性、传输距离、网络状态、客户端带宽和容忍度阈值为输入,进而决策出参与服务的最优节点集合,同时模型中设定了权重因子来均衡网络负载与资源代价....     

板料冲压过程的数值仿真与参数优化

采用有限元动态分析技术,采用HILL屈服准则,模拟了板料拉深成形的过程,结合实验拉深进行比较,模拟结果与实验数据符合.应用0.618-维搜索优化方法,在数值模拟中对压边力进行了优化,为实验中压边力的确定提供了参考数据.     

基于分组策略的多目标三维装箱算法

目的 针对现有三维装箱算法优化目标单一、优化效率低的问题,提出适用于求解大规模货物装载问题的多目标装箱算法,以提高装箱规划效率,确保货物运输安全。方法 考虑5种现实约束条件,以体积利用率和装载垛型重心偏移量为优化目标,建立多目标货物装载优化模型。采用拟人式装箱对货物进行预分组,减小决策空间,然后结合分组信息与装箱算法生成初始解;引入数据驱动的装箱交叉算子提高算法收敛性;设计多策略变异算子提高算法结果的多样性。结果 以公共数据集和真实航空货物数据作为实验数据进行实验。实验结果表明,在满足多种约束条件下,集装箱装载强异构货物平均体积利用率达到92.0%,重心位置空间偏移从20 cm减少到7.5 cm,并且算法运行时间减少了73.5%。结论 本文所提算法应用于求解大规模多目标三维装箱问题,提高了装箱质量和效率,可为三维装箱算法的工程应用提供参考。     

探索城市中压配电网络优化规划方向

随着社会市场经济的快速发展,社会的电能需求不断增大,我国的电力行业取得了一系列的进步与发展,这也对城市配电网络的优化提出了更高的要求,城市正常运转的重要保障就是配电网的良好运行,而中压配电网是城市配电网络中的重要组成部分,本文就主要结合我国城市中压配电网络优化规划的现状,对其优化规划工作予以简单分析探讨。     

基于Pareto最优解的零件制作方向优化研究

分析了快速成型工艺中零件制作方向对制件表面质量、所需支撑面积和零件制造时间的影响,分别建立了它们的优化数学模型。采用了基于Pareto最优解的多目标优化遗传算法NSGA-II进行优化计算,通过与单目标优化方法求得最优结果的对比,表明用多目标优化方法进行零件制作方向的优化计算,不仅可以求出比单目标方法更优的解,而且通过一次优化计算就可得到多个较优的零件制作方向。     

采用拓扑和几何调整的球面三角网格质量优化

以球面三角网格为研究对象,通过对三角网格进行拓扑优化和对顶点进行几何位置调整,实现了网格的质量优化。首先给出了球面三角网格顶点度的理想值,通过调整网格顶点的度使其达到这一理想值而实现了拓扑优化;然后使用离散点光滑插值（DSI）方法实现了对网格顶点的几何位置调整。最后对算法进行了验证。     

基于向量夹角的三角网格模型简化算法

提出以顶点向量夹角为剔除准则,运用顶点去除方法进行网格简化的算法。该算法首先计算每个网格顶点与其周围相邻顶点所形成的方向向量,然后根据方向向量的平均夹角来识别和简化网格中的平面区域,之后再以该顶点所处区域是否比较平坦为顶点去除限制条件,判断该顶点是否符合安全去除原则,这样可以保留特征顶点,进而保持物体的视觉特征。在顶点去除后,还需要对因此而形成的多边形进行三角形网格重建,以填补空洞。该算法在简化质量和简化速率方面取得了较好的平衡。     

一种改进粒子群算法的立体阵列优化方法

利用传统粒子群算法对立体阵列所有臂的阵元分布形式同时进行优化时,不仅耗时,而且易于收敛到局部解。为了解决这个问题,提出了一种改进粒子群算法(Improved Particle Swarm Optimization,IPSO)。改进算法采用并行计算思想,同时初始化多个粒子群,每个粒子通过优化一个臂(优化臂)的阵元参数达到"降维"的目的,使用线性递减惯性权重,对多个粒子群同时进行预优化,获得中间解。利用中间解构建一个"升维"的新粒子,使用最小惯性权重对新粒子继续优化,满足停止条件后输出。通过对5臂星形立体阵列进行优化设计,发现改进算法不仅耗时短,而且能够得到更优的结果,最后通过6个仿真实验讨论了所设计的阵列的指向特性。     

Metric-driven mesh optimization using a local simulated annealing algorithm

We report on results obtained with a metric-driven mesh optimization procedure for simplicial meshes based on the simulated annealing (SA) method. The use of SA improves the chances of removing pathological clusters of bad elements, that have the tendency to lock into frozen configurations in difficult regions of the model such as corners and complex face intersections, prejudicing the overall quality of the final grid. A local version of the algorithm is developed that significantly lowers the computational cost. Numerical examples illustrate the effectiveness of the proposed methodology, which is compared to a classical greedy Gauss–Seidel optimization. Substantial improvement in the quality of the worst elements of the grid is observed for the local simulated annealing optimization. Furthermore, the method appears to be robust to the choice of the algorithmic parameters. Copyright © 2006 John Wiley & Sons, Ltd.     

A multiobjective mesh optimization framework for mesh quality improvement and mesh untangling

We propose a multiobjective mesh optimization framework for mesh quality improvement and mesh untangling. Our framework combines two or more competing objective functions into a single objective function to be solved using one of various multiobjective optimization methods. Methods within our framework are able to optimize various aspects of the mesh such as the element shape, element size, associated PDE interpolation error, and number of inverted elements, but the improvement is not limited to these categories. The strength of our multiobjective mesh optimization framework lies in its ability to be extended to simultaneously optimize any aspects of the mesh and to optimize meshes with different element types. We propose the exponential sum, objective product, and equal sum multiobjective mesh optimization methods within our framework; these methods do not require articulation of preferences. However, the solutions obtained satisfy a sufficient condition of weak Pareto optimality. Experimental results show that our multiobjective mesh optimization methods are able to simultaneously optimize two or more aspects of the mesh and also are able to improve mesh qualities while eliminating inverted elements. We successfully apply our methods to real‐world applications such as hydrocephalus treatment and shape optimization. Copyright © 2013 John Wiley & Sons, Ltd.     

A blind proposed 3D mesh watermarking technique for copyright protection

ABSTRACT

Watermarking provides an efficient mechanism for copyright protection of digital media by embedding information in the object to identify the owner. This paper proposed a watermarking technique that can successfully embed a grey-scale image in a 3D mesh object. In our proposed technique, each three vertices of the 3D object can hide one pixel from the secret image. The experimental results showed that the proposed technique has better visual quality on both the watermarked object and the extracted secret image.     

Dynamic scaling in the mesh adaptive direct search algorithm for blackbox optimization

Blackbox optimization deals with situations in which the objective function and constraints are typically computed by launching a time-consuming computer simulation. The subject of this work is the mesh adaptive direct search (mads) class of algorithms for blackbox optimization. We propose a way to dynamically scale the mesh, which is the discrete spatial structure on which mads relies, so that it automatically adapts to the characteristics of the problem to solve. Another objective of the paper is to revisit the mads method in order to ease its presentation and to reflect recent developments. This new presentation includes a nonsmooth convergence analysis. Finally, numerical tests are conducted to illustrate the efficiency of the dynamic scaling, both on academic test problems and on a supersonic business jet design problem.     

An efficient multi‐layer planar 3D fracture growth algorithm using a fixed mesh approach

We present a planar three‐dimensional (3D) fracture growth simulator, based on a displacement discontinuity (DD) method for multi‐layer elasticity problems. The method uses a fixed mesh approach, with rectangular panel elements to represent the planar fracture surface. Special fracture tip logic is included that allows a tip element to be partially fractured in the tip region. The fracture perimeter is modelled in a piece‐wise linear manner. The algorithm can model any number of interacting fractures that are restricted to lie on a single planar surface, located orthogonal to any number of parallel layers. The multiple layers are treated using a Fourier transform (FT) approach that provides a numerical Green's function for the DD scheme. The layers are assumed to be fully bonded together. Any fracture growth rule can be postulated for the algorithm. We demonstrate this approach on a number of test problems to verify its accuracy and efficiency, before showing some more general results. Copyright © 2001 John Wiley & Sons, Ltd.     

A V-detector optimization algorithm

针对人工免疫系统中V-detector否定选择算法造成的检测器集合黑洞和检测器高重叠率等问题,借鉴生物免疫系统对免疫细胞的调节机制,提出了V-detector优化算法.该算法从父代产生候选检测器子代并通过检测器之间以及检测器与自体集合之间的亲和力对比更新检测器集合,使得检测器集合对非自体空间的覆盖更加合理.通过二维仿真实验和KDD CUP 99数据集实验测试,经优化后的检测器集合对非自体空间的覆盖性能有了显著提高,有效提高了系统的检测性能.     

A multigrid accelerated hybrid unstructured mesh method for 3D compressible turbulent flow

 A cell vertex finite volume method for the solution of steady compressible turbulent flow problems on unstructured hybrid meshes of tetrahedra, prisms, pyramids and hexahedra is described. These hybrid meshes are constructed by firstly discretising the computational domain using tetrahedral elements and then by merging certain tetrahedra. A one equation turbulence model is employed and the solution of the steady flow equations is obtained by explicit relaxation. The solution process is accelerated by the addition of a multigrid method, in which the coarse meshes are generated by agglomeration, and by parallelisation. The approach is shown to be effective for the simulation of a number of 3D flows of current practical interest. Sponsored by The Research Council of Norway, project number 125676/410 Dedicated to the memory of Prof. Mike Crisfield, a respected colleague