混沌优化水下地形匹配算法研究

为了解决迭代最近点算法的定位精度和实时性问题,提出了一种基于混沌优化搜索的迭代最近点算法.在该算法中,以参考导航系统测量位置为中心规划真实位置的搜索范围,从参考地形图上提取相应的地形高程数据,与对应经纬度位置一起定义成模式类,将模式识别的过程转化成函数优化问题,然后运用混沌优化算法搜索目标函数最小值进行全局寻优,从而获得匹配最近点.仿真结果表明,在保证寻优性能的情况下,可以减少匹配次数,提高识别速度,满足地形匹配精度和实时性的要求.     

结构优化的无初始随机复形法及其应用

本文主要考虑结构优化的理论和应用。为了得到一个更有效和快速的搜索结构设计最优解的技巧,作者提出了一个普遍的算法,称之为无初始随机复形法。运用这一方法能够形成一个计算最优解的自动迭代程序。作为该法的应用实例,文中讨论了几个平面框架结构的优化设计问题。通过这些实例可以显示出该法的下述三个优点:1.加快收敛速度;2.有利于求得总体极值;3.减少初始数据的输入,方便使用。     

基于差分进化和RBF响应面的混合优化算法

针对气动优化等昂贵优化问题,提出了一种基于差分进化和RBF响应面的混合优化算法HSADE,该方法结合了差分进化算法的强全局寻优能力和RBF响应面方法的快速局部搜索能力,能够同时有效地提高算法的局部搜索效率和全局寻优能力.对各子算法中的策略和逻辑进行了多项改进,提出和应用了基于双败淘汰赛的竞赛赛制和参数自适应等改进策略.对HSADE使用多个典型算例进行了测试,并横向对比了NSGA-II,MOPSO和多目标差分进化算法.测试结果表明,在大多数问题中HSADE在以世代距离表征的局部搜索效率和以超体积比表征的全局寻优能力两项指标上都优于其他算法,证实了以上混合策略及算法改进的有效性.将该算法应用于一个翼型优化问题和一个二维超声速喷管膨胀面优化问题,并横向对比未经改良的差分进化算法DE和另一种混合算法NARSGA,结果表明在接近1 000次的函数评估下,HSADE能相对其他算法进一步对翼型减阻0.5 count,在喷管优化中HSADE得到的结果也好于其他两种算法,表明该方法具有较强工程应用价值.     

基于RRT-GPM两阶策略的导弹编队协同突防最优轨迹快速设计

为了提高导弹编队的自主飞行能力,在考虑弹间协同相对运动关系(通信、避碰、探测)和突防硬/软约束的情况下,对弹群的多约束快速轨迹优化问题进行了研究。针对高斯伪谱法初值确定困难和快速搜索随机树法结果曲折不寻优难以满足动力学约束的不足,通过对高斯伪谱法快速性的分析和初值选取方法的研究,提出了快速搜索随机树+高斯伪谱法两阶快速轨迹优化策略,充分利用快速搜索随机树法的全空间搜索能力为高斯伪谱法提供寻优初始值,同时利用高斯伪谱法的快速性和最优性对快速搜索随机树法的结果进行平滑和进一步寻优,从而快速获得最优的弹群飞行轨迹。领-从弹编队飞行模式下的仿真结果表明,两阶策略能够快速获得满足各种约束的弹群最优飞行轨迹,优化时间约为单独高斯伪谱法所需时间的20%左右,很大程度上提高了轨迹优化的快速性和准确性,并且证明了不同约束条件对优化速度和优化结果的影响。     

基于正交基无单元Galerkin法和非线性规划的安定分析方法

基于安定分析的下限定理,用正交基无单元Galerkin法建立了交交载荷作用下理想弹塑性结构安定分析的下限计算格式.在给定载荷域的载荷角点所对应的载荷作用下,采用正交基无单元Galerkin法计算相应的虚拟弹性应力场.并且利用结构在正交基无单元Galerkin法弹塑性增量分析中平衡迭代结果计算得到自平衡应力场基矢量,然后由这些基矢量的线性组合模拟自平街应力场.安定分析问题最终被归结为一系列未知变量较少的非线性数学规划子问题,通过复合形法求解.算例表明该方法的计算结果是令人满意的,并且对初始复合形顶点和用于构造自平衡应力场基矢量的载荷增量是非常不敏感的.     

工程结构优化的进化策略-高斯过程协同优化方法

针对采用仿生全局优化方法进行复杂工程结构优化时数值计算量浩大导致的计算代价过高的公开问题,将自适应协方差矩阵进化策略(CMAES)全局优化算法、高斯过程(GP)机器学习技术与有限元方法相结合,提出了基于自适应协方差矩阵进化策略-高斯过程协同优化算法(CMAES-GP)的结构优化方法。该方法利用全局寻优性好且寻优效率高的CMAES算法进行全局最优搜索,当搜索进入局部寻优阶段时,采用回归性能优秀的GP模型对适应度函数进行动态拟合,进而利用GP模型替代有限元分析进行个体适应度评价,以减小局部寻优阶段的有限元重分析次数,从而实现有效降低工程结构优化计算代价的目的。算例研究表明,与传统结构优化方法相比较,本文方法具有全局性好、计算效率高的优点。     

机械系统动力优化设计的自适应混合遗传算法

针对机械系统动力优化设计问题的特点，本文提出了一个自适应混合遗传算法。该方法将目适应控制参数调整策略、小生境技术和单纯形法有机地融入遗传算法，较为有效地解决了基本遗传算法的过早收敛和局部搜索能力弱的问题，提高了算法全局寻优的可靠性和收敛速度，为解决机械系统动力优化设计问题提供了一种可靠、有效和易用的优化方法。一个五自由度汽车悬挂系统的动力优化设计实例验证了算法的效率、可靠性和实用性。     

非线性函数的混沌优化方法比较研究

已有的混沌优化方法几乎都是利用Logistic映射作为混沌序列发生器，而Logistic映射产生的混沌序列的概率密度函数服从两头多、中间少的切比雪夫型分布，不利于搜索的效率和能力。为此，首先根据Logistie映射混沌轨道点密度函数的特点，建立改进的混沌-BFGS混合优化算法。之后，考虑到Kent映射混沌轨道点密度为均匀分布，建立了基于Kent映射的混沌-BFGS混合优化算法。然后对五种混合优化方法——不加改进的和改进的基于Logistic映射的混沌-BFGS法，基于Kent映射的混沌-BFGS法，Monte Carlo试验-BFGS法，网格-BFGS法进行了研究，分别对3个低维和2个高维非线性复杂测试函数进行优化计算，对它们的全局优化计算效率和寻优能力做了比较，并探讨了混合优化方法全局优化性能差异的原因。结果表明，混沌优化方法是与Monte Carlo方法类似的一种随机性试验优化方法。而且，这类优化方法的计算性能至少与以下因素有关：混沌／随机序列的统计性质，优化问题全局最优点位置。     

非概率区间模型可靠性指标的梯度投影算法

考虑不确定参数为区间变量,研究求解非概率可靠性指标的有效搜索算法.基于函数梯度法的基本思想,构造搜索方向,建立迭代算法格式,将传统的用于概率可靠性分析的梯度投影法用于非概率可靠性指标的求解.当收敛点为非最可能失效点时,提出了空间降维算法,并给出了整个搜索算法的计算步骤.通过数值算例,验证了本文提出的搜索迭代算法的有效性和正确性.     

基于粒子群-AK-MCS法的结构可靠性分析

Kriging代理模型由于其良好的非线性拟合能力,在可靠性分析领域得到了广泛的应用。为提高Kriging模型的建模效率,本文提出一种混合粒子群算法的AK-MCS法,该方法在保证模型精度的前提下减少了构建代理模型时的迭代次数,且提高了模型的全局寻优能力。以一10杆桁架结构为研究对象,通过建立结构控制位移与杆件截面面积和集中荷载之间的代理模型,快速求解桁架结构的失效概率。研究表明,本文方法有效提高了Kriging模型建模效率和建模精度,在计算复杂工程结构时具有一定的可行性。     

类电磁机制算法研究与改进

针对原算法中初始种群不均匀、局部搜索随机性强及移动公式效率低等问题,提出了一种改进的类电磁机制算法。采用随机化均匀设计方法构造初始种群,将混沌搜索与试探性移动方法相结合进行局部搜索,运用改进后的公式计算粒子之间的合力,将遗传变异思想融入移动公式来更新粒子。实验结果表明,改进后的算法具有更好的收敛效果和更高的求解精度。     

A discrete nonlinear stepping optimization method and its application

Most of the practical design variables should always be discrete quantity within engineering optimization design problems. To obtain the true optimization solution, a discrete optimization method must be used. In this paper, a new method called step optimization search method is presented to solve the discrete quantity mathematic programming problems. The basic idea of this method is to find out an initial feasible point and then to search the optimum point step by step in the neighbouring region of this point so as to obtain an improved new discrete point. Respectively, the new point can be taken as initial one, and the whole process can be carried out once more until the optimum solution of the problem is obtained. Some results of numerical examples of practical problems show that this new method can solve problems quickly and simply and can be applied in a lot of engineering design problems.     

A fast and reliable overset unstructured grids approach

A cell-centred overset unstructured grids approach is developed.In this approach,the intergrid boundary is initially established based on the wall distance from the cell centre,and is then optimized.To accelerate the intergrid-boundary definition much more,a neighbor-toneighbor donor search algorithm based on advancing-front method is modified with the help of minimum cuboid boxes.To simplify the communications between different grid cell types and to obtain second-order spatial accuracy,a new interpolation method is constructed based on linear reconstruction,which employs only one layer of fringe cells along the intergrid boundary.For unsteady flows with relative motion,the intergrid boundary can be redefined fast and automatically.Several numerical results show that the present dynamic overset unstructured grids approach is accurate and reliable.     

Optimum design of composite laminates

A new procedure for the optimum layup design of composite laminates is described in this paper. In this method the global optimum search and local relaxing constraints are adequately combined together. The design variables are divided and applied in separate processes. A 16-node hybrid semi-Loof element model is used in the global structure analysis. The iterative complex method is adopted in the optimization. The method is suitable for the minimum weight design of a laminate subjected to the strength and stiffness constraints under multiple loading. The numerical results demonstrate the high efficiency and reliability of the present method.The project was supported by National Natural Science Foundation of China     

负高斯曲率曲面薄壁管吸能特性研究

为设计出具备优良吸能特性的薄壁结构,提出一种新型负高斯曲率曲面圆形横截面薄壁管(negative Gaussian curvature surface circular tube, NGC-C)。利用经验证的有限元分析方法对其进行轴向动态冲击模拟,提取各项性能指标,借助复杂比例评估法(complex proportion assessment, COPRAS)将其与传统薄壁吸能结构进行了综合性能对比。采用拉丁超立方抽样法从设计空间中提取样本点并获取各样本点对应性能响应值,建立代理模型。基于该代理模型,借助改进非支配排序遗传算法(non-dominated sorting genetic algorithm, NSGA-Ⅱ)对其进行了多目标优化设计。结果表明:NGC-C综合性能优于传统薄壁吸能结构,经优化后比吸能提高了16.47%,有效压溃长度降低了12.40%,质量减少了20.18%。将负高斯曲率曲面形态引入薄壁管构型,能够提高薄壁管的耐撞性和轴向抗变形能力。     

引入退火机制的智能单粒子算法在复杂边坡最危险滑动面搜索中的应用

复杂边坡的安全系数可能存在多个局部极小值点,如何确定边坡的最小安全系数是复杂边坡稳定性分析中的一个关键问题。本文结合简化Bishop法,采用一种新的启发式全局优化算法——智能单粒子算法(ISPO)来搜索复杂边坡的最危险滑动面。为帮助该算法快速跳出局部极值点,本文将模拟退火(SA)机制引入到智能单粒子算法中,结合了两种算法各自的优点,提出了引入退火机制的智能单粒子算法SA-ISPO。将本文提出的SA-ISPO算法用于搜索两个复杂边坡的最危险滑动面,并与其它方法相比较,验证了SA-ISPO算法的优越性,该算法搜索效率高,计算结果不受搜索范围的影响,是一种较好的全局优化算法。     

An optimal method for seismic drift design of concrete buildings using gradient and Hessian matrix calculations

This paper describes a novel seismic optimal design method for the reinforced concrete frame. First, an optimal mathematical model with time-dependent constraints, i.e., inter-story drift constraints, is established for achieving minimum weight design. Second, the inequality constraint problem with time-dependent constraints is converted into a sequence of appropriately formed unconstrained problems using the integral interior point penalty function method. Third, an efficient algorithm of the first and second derivatives of the inter-story drift with respect to design variables is formulated based on Newmark-β method. Gradient and Hessian matrix of the integral interior penalty function are also computed. Fourth, Marquardt’s method is employed to solve a sequence of unconstrained problems. Finally, the minimum weight design of a three-story, two-bay planar frame is demonstrated using the new optimization method and the augmented Lagrange multiplier method. The comparative results show the seismic optimal design method presented in this paper is more efficient than the augmented Lagrange multiplier method in terms of computational time. The proposed new method is an effective and efficient approach for minimum weight design of the reinforced concrete frames subjected to earthquake excitation.     

Size effect of lattice material and minimum weight design

The size effects of microstructure of lattice materials on structural analysis and minimum weight design are studied with extented multiscale finite element method（EMsFEM） in the paper. With the same volume of base material and configuration, the structural displacement and maximum axial stress of micro-rod of lattice structures with different sizes of microstructure are analyzed and compared.It is pointed out that different from the traditional mathematical homogenization method, EMsFEM is suitable for analyzing the structures which is constituted with lattice materials and composed of quantities of finite-sized micro-rods.The minimum weight design of structures composed of lattice material is studied with downscaling calculation of EMsFEM under stress constraints of micro-rods. The optimal design results show that the weight of the structure increases with the decrease of the size of basic sub-unit cells. The paper presents a new approach for analysis and optimization of lattice materials in complex engineering constructions.     

基于最小搜索超椭球的GNSS模糊度固定及检验方法

为进一步简化GNSS模糊度解算流程,降低计算复杂度,重点提高LAMBDA算法的搜索效率,对模糊度解算作出以下改进:1)模糊度检验采用后验概率检验方法,并对其目标函数进行适当简化;2)把简化后的目标函数嵌入模糊度搜索过程,省去了单独的模糊度检验步骤;3)推导了模糊度空间最小搜索超椭球,把搜索区域限制在该超椭球中,缩小了搜索范围,从而大大降低了搜索复杂度。用三组实测数据实验比较了新方法和传统的LAMBDA方法,结果显示新方法搜索复杂度降低普遍在30%左右,最高可接近60%。理论推导和实验结果均证明了新方法的高效性。     

An improved genetic algorithm and its applications to the optimisation design of an aspirated compressor profile

Genetic algorithm (GA) is a widely used method for numerical optimisation owing to their good global search ability; however, their local search ability has an obvious shortcoming. To improve local search ability, this paper introduces a simplex method and combines it with a GA to form an improved genetic algorithm (IGA). In the IGA, at each generation of the original GA, high‐fitness individuals are selected as vertices of a simplex, and then a one‐dimensional search within the simplex is conducted to obtain the most‐fit individuals while replacing the inferior ones. Typical test functions show that the IGA can effectively improve the optimisation effect over that of the original GA. To further verify the IGA's practicability, an aspirated compressor profile is optimised with profile, suction flow rate and suction flow location as coupled design parameters. The results again show that the IGA has a better optimising effect than the GA. In addition, it is also verified that coupling the profile and suction flow parameters results in a design that outperforms the uncoupled design; therefore, designing an aspirated compressor blade by arranging suction flow on a conventional blade without considering suction flow is not a good method. Copyright © 2015 John Wiley & Sons, Ltd.