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.     

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。     

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。     

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。     

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。     

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.     

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 predictor-corrector contouring algorithm for isoparametric 3D elements

This paper describes a new contouring algorithm for isoparametric elements which can be used to map three-dimensional scalar fields. The contours are generated on arbitrary planes intersecting finite element structures. Tracing element contour lines is accomplished by an accurate predictor-corrector technique. A method of finding starting points for the algorithm on the boundary of the elements is also given.     

A fuzzy-controlled Hooke-Jeeves optimization algorithm

This article presents an approach to enhance the Hooke-Jeeves optimization algorithm through the use of fuzzy logic. The Hooke-Jeeves algorithm, similar to many other optimization algorithms, uses predetermined fixed parameters. These parameters do not depend on the objective function values in the current search region. In the proposed algorithm, several fuzzy logic controllers are integrated at the various stages of the algorithm to create a new optimization algorithm: Fuzzy-Controlled Hooke-Jeeves algorithm. The results of this work show that incorporating fuzzy logic in the Hooke-Jeeves algorithm can improve the ability of the algorithm to reach an extremum in different typical optimization test cases and design problems. Sensitivity analysis of the variables of the algorithm is also considered.     

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     

格网中p-cycles重配置的快速实现算法

提出了一种用于双链路故障恢复和为动态业务提供保护的p-cycles重配置启发式算法.该算法可以提供网络生存性设计和网络管理的高效性和简洁性,并能提供快速的恢复操作.仿真结果表明,这种算法用于双链路故障恢复的重配置容量冗余度可达74%,平均计算时间为48ms;用于增量重配置的双故障冗余度为118%,计算时间为81ms.基于该算法的业务恢复可以满足大多数业务的最低可中断时间要求.分析表明该算法亦适用于动态业务的p-cycles重配置.     

A surrogate-model based multi-modal optimization algorithm

In this article a new algorithm for optimization of multi-modal, nonlinear, black-box objective functions is introduced. It extends the recently-introduced adaptive multi-modal optimization by incorporating surrogate modelling features similar to response surface methods. The resulting algorithm has reduced computational intensity and is well-suited for optimization of expensive objective functions. It relies on an adaptive, multi-resolution mesh to obtain an initial estimation of the objective function surface. Local surrogate models are then constructed and used to generate additional trial points around the local minima discovered. The steps of mesh refinement and surrogate modelling continue until convergence is achieved. The algorithm produces progressively accurate surrogate models, which can be used for post-optimization studies such as sensitivity and tolerance analyses with minimal computational effort. This article demonstrates the effectiveness of the algorithm using comparative optimization of several multi-modal objective functions, and shows an engineering application of the design of a power electronic converter.     

Adaptive analysis of 3D cavity flow using hierarchical mesh

In this paper, we present an ultra-high-speed adaptive meshing using a hierarchical method, which has been often used in the computer graphics field. If the hierarchical mesh is used, meshes can be changed very quickly. We have applied this meshing successfully to the adaptive analysis of 3D cavity flow, interpolating the values (flow velocity, pressure or error) at the nodes after re-meshing from those before re-meshing without reconstruction of the hierarchical data structure.     

A new first-order interior feasible direction method for structural optimization

A new interior feasible direction method for optimization problems with linear objective functions but non-linear constraints is proposed. The method is particularly suitable for weight minimization problems in structural design where the design variables are the cross-sectional areas of members and arbitrary stress and displacement constraints are applied. Four truss structures are analysed and in each case the minimum weight consistent with or lower than that currently available in the literature is achieved. Although still expensive in its current version, the method is comparable in cost and robustness with other methods such as the ‘trust region’ multiplier method. Apart from one tolerance value, a reconnaissance parameter needs to be specified. The fact that the same value of the parameter was used for all the examples, and that the method is relatively insensitive to the choice thereof, confirms the robustness of the method.