Non-probabilistic Robust Optimal Design Method

For the purpose of dealing with uncertainty factors in engineering optimization problems, this paper presents a new non-probabilistic robust optimal design method based on maximum variation estimation. The method analyzes the effect of uncertain factors to objective and constraints functions, and then the maximal variations to a solution are calculated. In order to guarantee robust feasibility the maximal variations of constraints are added to original constraints as penalty term; the maximal variation of objective function is taken as a robust index to a solution; linear physical programming is used to adjust the values of quality characteristic and quality variation, and then a bi-level mathematical robust optimal model is coustructed. The method does not require presumed probability distribution of uncertain factors or continuous and differentiable of objective and constraints functions. To demonstrate the proposed method, the design of the two-bar structure acted by concentrated load is presented. In the example the robustness of the normal stress, feasibility of the total volume and the buckling stress are studied. The robust optimal design results show that in the condition of maintaining feasibility robustness, the proposed approach can obtain a robust solution which the designer is satisfied with the value of objective function and its variation.     

Multiple stiffness topology optimizations of continuum structures

This paper presents a new multi-objective topology optimization algorithm for continuum structures under multiple loading cases. An expert evaluation method of weights based on grey system theory is proposed to calculate the objective weights when the compromise programming approach is employed as a multi-objective optimization scheme converting the multi-objective problem to a single objective problem. A modified updating scheme with a self-adaptive move limit for design variables is also suggested, SIMP is regarded as density-stiffness interpolation scheme and the optimality criteria method is used as the optimizer. Numerical instabilities, such as checkerboards and mesh dependencies, are also discussed. The validities of these methods in this paper are demonstrated by some numerical applications.     

基于遗传算法的轴流汽轮机级效率优化

提出一种基于遗传算法的轴流汽轮机级通流部分的优化设计方法。该方法以轴流汽轮机级效率为优化目标,利用遗传算法通过使汽轮机级在满足一系列约束条件下效率最大化来搜索最佳的通流部分几何参数和气流参数。级效率计算和约束条件分析由一个轴流汽轮机级设计工况计算程序得到。遗传算法中每个个体的适应度由级效率和由约束条件得到的罚函数项组成。该方法应用于某型机第一级通流部分的优化设计,优化结果显示,可求得具有最佳效率的通流部分几何形状和气流参数。     

Geometrically constrained isogeometric parameterized level-set based topology optimization via trimmed elements

In this paper, an approach based on the fast point-in-polygon (PIP) algorithm and trimmed elements is proposed for isogeometric topology optimization (TO) with arbitrary geometric constraints. The isogeometric parameterized level-set-based TO method, which directly uses the non-uniform rational basis splines (NURBS) for both level set function (LSF) parameterization and objective function calculation, provides higher accuracy and efficiency than previous methods. The integration of trimmed elements is completed by the efficient quadrature rule that can design the quadrature points and weights for arbitrary geometric shape. Numerical examples demonstrate the efficiency and flexibility of the method.     

An interactive algorithm for multi-objective flow shop scheduling with fuzzy processing time through resolution method and TOPSIS

This paper develops a method for solving a multi-objective flow shop scheduling in a fuzzy environment where processing times are fuzzy numbers. The objective functions are designed to simultaneously minimize the makespan (completion time), the mean flow time, and the machine idle time. For each objective function, a fuzzy subset in the decision space whose membership function represents the balance between feasibility degree of constraints and satisfaction degree of the goal is defined. Then, technique for order preference by similarity to an ideal solution (TOPSIS) method finds the nondominated solution in a multiple objective state. The TOPSIS method and the interactive resolution method are integrated in the proposed method to solve the multi-objective flow shop scheduling problem. One of the new contributions of this research is combining these two methods in solving this problem. The proposed algorithm provides a way to find a crisp solution for the fuzzy flow shop scheduling in a multi-objective state. Also, the proposed method yields a reasonable solution that represents the balance between the feasibility of a decision vector and the optimality for an objective function by the interactive participation of the decision maker in all steps of decision process. Application of the proposed method to flow shop scheduling is shown with two numerical examples. The results show that the algorithm could be applied for determining the most preferable sequence by finding a nondominated solution for different degrees of satisfaction of constraints, and with regard to objective value, where processing time is fuzzy.     

动态电容层析成像图像重建算法

提出了融合ECT测量信息和被测对象动态演化信息的新型图像重建模型;基于Tikhonov正则化方法,建立一个同时考虑了ECT测量信息、被测对象动态演化信息、时间与空间约束的新型图像重建目标泛涵,将图像重建问题转化为最优化问题;提出了集成分裂Bregman迭代法优势的新型算法求解该目标泛涵。数值仿真结果表明,所提出的图像重建算法其图像重建质量均优于OIOR算法、STR算法及PLI算法;同时由于所提出的图像重建算法同时考虑了测量数据和重建模型的不精确性,其抵抗测量噪声的能力得以提高。     

基于约束理论和系统动力学的生产系统再造方法

针对生产系统再造过程中出现的问题,将约束理论和系统动力学引入生产系统再造中.通过分析三者的相互联系,提出了基于约束理论和系统动力学的生产系统再造方法.该方法通过改进建模方法,强调了"人"的因素重要性,利用解决问题树、资源使用树和约束转移矩阵,克服再造过程中由于约束转移带来的问题,避免追求短期最优化的问题,从系统上和战略上对生产系统进行再造.另外,扩展了约束理论,提出了全面约束管理的思路,该思路从新的角度对生产约束进行认识和管理,强调以约束为管理对象,并通过对约束的管理,提高企业的运作效率,进而提出建立起约束监督、预警机制,对约束实行全方位的管理.最后,运用实证分析对所提出的方法进行了验证.     

约束阻尼板双线性材料插值法拓扑动力学优化

为减小阻尼板质量并提高减振性能,研究了结构动力学优化技术。构建了以移动常数与模态损耗因子差值为目标、阻尼层单元密度为拓扑变量、阻尼层体积用量及振动模态频率为约束的阻尼板优化模型。利用序列凸规划法构造目标函数的凸性逼近式,采用拉格朗日乘子法解算逼近函数,以获取全局优化的阻尼层布局。利用模态损耗因子与模态应变能的本构关系推导目标函数关于拓扑设计变量的灵敏度,基于K-T条件构造拓扑变量迭代式。引入双线性插值函数惩罚拓扑变量并使其值聚集于0或1,编写并实现了悬臂阻尼板优化程序。当阻尼层体积用量控制在50%时,1阶模态损耗因子增大52.29%,灰度单元占比1.78%。阻尼板谐响应分析表明优化构形具良好减振特性。双线性插值优化既能充分发挥阻尼层的耗能效力又可大幅减少灰度阻尼单元数。     

基于加权应变能的某ATV车身拓扑优化设计

以极限弯曲和扭转工况的加权应变能最小为目标函数,以设计区域的体积分数为约束,以设计区域的材料密度为设计变量,建立基于加权应变能的拓扑优化模型。并对某ATV车身进行拓扑优化设计,得到了结构的载荷传递路径,验证了该方法的可行性。     

A Study for robustness of objective function and constraints in robust design optimization

Since randomness and uncertainties of design parameters are inherent, the robust design has gained an ever increasing importance in mechanical engineering. The robustness is assessed by the measure of performance variability around mean value, which is called as standard deviation. Hence, constraints in robust optimization problem can be approached as probability constraints in reliability based optimization. Then, the FOSM (first order second moment) method or the AFOSM (advanced first order second moment) method can be used to calculate the mean values and the standard deviations of functions describing constraints and object. Among two methods, AFOSM method has some advantage over FOSM method in evaluation of probability. Nevertheless, it is difficult to obtain the mean value and the standard deviation of objective function using AFOSM method, because it requires that the mean value of function is always positive. This paper presented a special technique to overcome this weakness of AFOSM method. The mean value and the standard deviation of objective function by the proposed method are reliable as shown in examples compared with results by FOSM method.     

考虑约束松弛的柔性流水调度研究

针对柔性流水车间作业调度问题,考虑加工批量约束松弛和瓶颈工序顺序松弛2种情形,抽取出相应的新型柔性流水车间调度问题,建立了最小化最大完工时间的数学模型,提出了改进的单亲遗传算法,进行了优化求解,得到了不同约束松弛情况下的最优调度方案。通过算例仿真,验证了所提方法的有效性。     

A fairly general method for optimum synthesis of planar mechanismsUne methode generale pour la synthese optimale des mecanismes coplanaires

This article introduces a new method for optimum synthesis of planar mechanisms with lower pairs. The method uses a single objective function for any mechanism and for any type of synthesis, making it possible to perform even mixed syntheses. It is also possible to consider a wide variety of constraints and initial conditions. The error minimization process is carried out on two levels, and techniques which have been proved efficient for the problem under consideration are described. Finally, the article presents several examples which have been solved by the proposed method.     

Supplier selection by the new AR-IDEA model

Traditionally, supplier-selection models have been based on cardinal data with less emphasis on ordinal data. However, with the widespread use of manufacturing philosophies such as just-in-time (JIT), emphasis has shifted to the simultaneous consideration of cardinal and ordinal data in the supplier-selection process. The application of data envelopment analysis (DEA) for supplier-selection problems is based on total flexibility of the weights. However, the problem of allowing total flexibility of the weights is that the values of the weights obtained by solving the unrestricted DEA program are often in contradiction to prior views or additional available information. The objective of this paper is to propose a new pair of assurance region-imprecise data envelopment analysis (AR-IDEA) model for selecting the best suppliers in the presence of both weight restrictions and imprecise data. A numerical example demonstrates the application of the proposed method.     

A fuzzy group decision support system for multifacility location problems

Multifacility location problems are considered to find optimal location of new facilities with respect to a set of existing ones. Generally, the objective of the problem is minimizing the total distance traveled between facilities. In this paper, a methodology is proposed for multifacility location problem, investigating decision makers’ opinion as a group decision-making problem. Since uncertainty of information in decision-making environment exists, we consider it by applying a fuzzy set theory. At first, the problem is formulated as a fuzzy multiobjective model. After introducing a decision support system based on fuzzy inference system and using fuzzy analytic hierarchy process approach for obtaining weights between facilities, at last, a two-phase fuzzy linear programming considering the concept of degree of satisfaction of each objective is applied to solve the multiobjective problem. Finally, a numerical example is given to illustrate the proposed method and a sensitivity analysis is expressed to show capability of the method for generating different optimal solutions based on the importance of each decision maker’s opinion.     

时序约束条件下序列测试建模方法

时序约束的描述是测试序列生成前必须面对的问题,但是目前还没有完善的方法能够对时序约束进行描述,为此提出了一种时序约束序列测试建模方法。该建模方法中提出了状态转移允许区间,使得可以对转移发生时前一个状态的连续出现次数进行描述。针对目前欠缺能够有效评价测试序列目标覆盖程度的方法的问题,通过引入核函数来评价测试序列的目标覆盖程度对该问题给予了解决。最后利用提出的建模方法对实例进行建模,验证了建模方法的有效性和可行性。     

具有某阶频率约束的试验架设计

为了避开试验架的加载设备的激振频率与试验架的某一阶固有频率耦合，提高试验系统工作的可靠性、安全性和动态性能，针对试验架的结构特点，对试验架建立了具有某阶固有频率约束、以重量最小化为目标函数的优化模型。通过有限元建模、灵敏度分析和采用逐次线性规划求解优化问题，对试验架的主要构件的截面参数进行了优化。结果表明，该方法具有简单、收敛快，具有一定的工程价值。     

基于自适应蚁群算法的工艺路线优化

针对计算机辅助工艺设计中最优方案选择,提出一种以制造资源更换率最低为目标的自适应蚁群优化方法(Adaptive ant colony algorithm,AACA)。通过分析零件特征,根据精度要求对制造特征进行分解,提出加工元概念。加工元被定义为特定的制造特征、加工阶段、加工方法、制造资源、装夹位置的集合,工艺路线的确定被转换为对加工元的优化顺序安排问题。以制造特征之间的几何位置约束,各加工阶段的先后顺序约束为基本元素,构造加工元优选约束矩阵,给出基于优选约束矩阵的加工元优选原则。在加工元优先顺序约束和可用制造资源的共同约束下,将缩短加工周期、提高加工质量和降低加工成本的综合目标表达为制造资源更换率最低,进行优化目标函数的数学建模。指出加工元优化排序可类比旅行商问题,并选择AACA进行优化求解。实例分析表明提出的方法可以可靠和有效地得到符合生产实际的工艺路线。     

基于模态控制的结构/控制一体化优化设计

先分析了结构主动控制的模态控制。从结构与控制器一体化优化设计的角度出发 ,提出了以结构的质量和控制能量最小化为优化目标、以基频和结构的动响应为约束的联合优化设计模型。并对该优化设计模型进行了一定的简化处理 ,采用改进的拓扑组方法进行结构的集成拓扑优化设计。数值算例的结果表明 ,结构 /控制一体化优化设计是可行且有效的。     

油泵柱塞组合件收口强度稳定性试验分析

在多指标试验设计综合加权评分法中，各项试验指标权重的确定是极其重要的，它直接关系到分析结果的合理性、可靠性。为了对指标的赋权达到主观与客观的统一，文中采用一种兼顾主观偏好和客观信息的综合权重赋值法，为油泵柱塞组合件收口强度稳定性试验的分析结果客观、真实寻找一条新途径。     

最近邻实例检索相似度分析

针对最近邻实例检索中实例属性相似度和权重的计算问题,给出了区间值属性相似度的计算模型,并将各种属性类型的相似度计算方法加以统一,提出了基于相似度离差信息的客观赋权方法,并以组合权重计算实例相似度.该方法已应用于基于实例推理的导弹概念设计之中,结果表明,所提出的权重计算方法更有利于实例的检索.