武器系统研制方案的多层次灰关联综合评价

为了更好地解决多层次多目标的综合评价问题,文中将层次分析法和灰关联综合评估法两种系统评价方法结合起来,提出一种多目标多层次加权灰关联综合评估方法。先建立综合评估模型,再通过多层次灰关联评估,获取了加权灰关联度。根据关联度大小,对三种武器系统研制方案进行了优劣排序。实例应用结果证明,该方法综合了两种方法的优点,使用简便,切实可行,适合于解决多方案的优选问题。     

Optimizing the design of automotive S-rail using grey relational analysis coupled with grey entropy measurement to improve crashworthiness

The optimization of the crashworthiness and lightweight design of S-rail extracted from the frontal body in white was studied in this paper. A physical test was conducted to verify the validity of S-rail model and then an implicit parameterization model was built based on the S-rail model using the software SFE-CONCEPT. Based on the implicit parameterization modeling, a steel-aluminum S-rail was designed to reduce the peak collision force (PCF) and increase the specific energy absorption (SEA) under the condition that the total weight (M) of S-rail does not increase. L₁₆ (4⁵) Taguchi array was used to collect sample points which will be prepared for the optimization design. The experimental results were analyzed through grey relational analysis (GRA) coupled with grey entropy measurement method. The multi-objective optimization was then converted into a single objective optimization problem based on the grey relational grade. The optimal combination of design parameters for S-rail was obtained using the proposed method. Meanwhile, a comparison was presented between the proposed method and other extensively used methods (i.e. NSGA-II, MOPSO, and ASA), and the proposed method reduces the PCF and M to 26.81% and 46.01% respectively, and increases the corresponding SEA by 176.06%. Moreover the computational cost can be reduced by 143.5% at least when compared with other extensively used methods. Therefore, the hybrid method can efficiently improve the crashworthiness and reduce the computational cost during the design process of S-rail.     

一种多目标优化问题的理想灰色粒子群算法*

针对逼近理想解的排序方法对Pareto前端的距离跟踪以及灰色关联度能够很好地分析非劣解集曲线与Pareto最优解集曲线的相似性,提出了一种求解多目标优化问题的理想灰色粒子群算法。该算法利用理想解理论与灰色关联度理论来求解粒子与理想解之间的相对适应度和灰色关联度系数,把两者的和定义为相对理想度,通过相对理想度来判别粒子的优劣,以确定个体极值和全局极值。通过四组不同类型的基准函数测试算法性能,并与目标加权法和灰色粒子群算法比较分析,结果表明该算法能够较好地收敛到Pareto最优解集,不但具有较好的收敛性和分布     

网格环境下基于Weka4WS的分布式聚类算法*

Weka4WS采用WSRF技术用于执行远程的数据挖掘和管理分布式计算,支持分布式数据挖掘任务。基于Weka4WS和网格环境,尝试了一种新的分布式聚类方法,并成功地将其嵌入到Weka4WS框架中,借助Weka Library实现分布式数据挖掘算法,同时引入了距离代价和混合概率的概念,将网格与Web服务技术融合,以分布式问题求解环境和开源数据挖掘类库Weka为底层支持环境,构建了网格环境下面向服务的分布式数据挖掘体系,并以基于Weka4WS的分布式聚类算法验证了算法的有效性和体系结构的可行性。     

基于灰熵并行分析法的多目标作业车间调度优化

提出利用信息熵理论与灰色关联分析法并行地处理多目标优化问题,将多目标优化的目标值构成数据序列,挖掘序列关系实现多目标优化。首先,并行的对目标值序列计算灰关联系数以及熵值权重,之后将信息熵与灰关联系数结合计算灰熵并行关联度,建立灰熵并行分析法。最终,利用灰熵并行关联度作为优化算法的适应值计算策略,以该策略引导智能优化算法进化。建立作业车间调度问题的三目标优化模型,以灰熵并行分析法为基础,分别应用差分算法、遗传算法解决三目标作业车间调度问题,验证新方法的可行性。实验表明：新方法均能使两算法收敛且得到分布均匀的 Pareto 前端,表明其有效和可靠。同时,差分算法得到的解较遗传算法的解具有明显的优势。     

基于灰色关联和遗传算法的供应链伙伴选择

供应链伙伴选择是一个典型的多目标决策问题,本文提出一种解决该问题的新方法.该方法分为两个阶段:第一,运用灰色关联分析的思想,将多目标决策转换为单目标决策模型.第二,对于得到的单目标决策模型设计自适应遗传算法求解,所得的最优解就是伙伴选择的多目标决策模型的最优解.为说明该方法的可行有效,进行了实际算例的求解.     

Structural optimization in design planes

A new optimal design procedure based on successive optimization in design planes is presented. It is intended to improve the convergence properties of the solution process and to reduce the computational effort. Optimization is carried out at each iteration cycle in a two-dimensional design plane, formed by the current design and a selected direction vector in the design space. Applying the scaling operation, optimization in a design plane is reduced to a problem of a single independent variable. The computational effort is further reduced by introducing approximate behaviour models for the selected design planes.

The procedures of selecting a design plane and optimization in the plane are repeated until the final optimum is achieved. Since all intermediate designs are feasible, the solution process can always be terminated with an improved feasible design. Various methods can be employed to introduce design planes; some of them are investigated in this study.

Numerical experience with the proposed procedure shows that the final optimum can be achieved in a small number of iteration cycles. This feature is particularly important for problems where other algorithms fail to arrive at the optimum in a reasonable number of iterations.     

基于灰色层次分析法的老年人APP 用户体验评价研究

为了提高老年人APP 的用户体验水平,提出一种基于灰色层次分析法(AHP)的老 年人APP 用户体验评价模型。首先,构建用户体验的评价体系;接着,通过AHP 计算评价指 标的权重;最后,采用灰色关联分析法(GRA)将用户体验的评价指标整合为灰色关联度,从而 根据灰色关联度选择最优方案。以移动医疗APP 作为案例,结果表明基于灰色AHP 的APP 用 户体验评价模型可以有效地评价老年人APP 的用户体验水平,为设计决策提供依据。     

A mixed GA-PSO-based approach for performance-based design optimization of 2D reinforced concrete special moment-resisting frames

A mixed genetic algorithm and particle swarm optimization in conjunction with nonlinear static and dynamic analyses as a smart and simple approach is introduced for performance-based design optimization of two-dimensional (2D) reinforced concrete special moment-resisting frames. The objective function of the problem is considered to be total cost of required steel and concrete in design of the frame. Dimensions and longitudinal reinforcement of the structural elements are considered to be design variables and serviceability, special moment-resisting and performance conditions of the frame are constraints of the problem. First, lower feasible bond of the design variables are obtained via analyzing the frame under service gravity loads. Then, the joint shear constraint has been considered to modify the obtained minimum design variables from the previous step. Based on these constraints, the initial population of the genetic algorithm (GA) is generated and by using the nonlinear static analysis, values of each population are calculated. Then, the particle swarm optimization (PSO) technique is employed to improve keeping percent of the badly fitted populations. This procedure is repeated until the optimum result that satisfies all constraints is obtained. Then, the nonlinear static analysis is replaced with the nonlinear dynamic analysis and optimization problem is solved again between obtained lower and upper bounds, which is considered to be optimum result of optimization solution with nonlinear static analysis. It has been found that by mixing the analyses and considering the hybrid GA-PSO method, the optimum result can be achieved with less computational efforts and lower usage of materials.     

求解人力资源分配问题的多目标微粒群优化算法*

提出一种改进的多目标微粒群优化算法来求解人力资源分配问题.通过对种群进行正交初始化,保证了个体在整个可行解空间上的均匀分散,使得算法能够在整个可行解空间上进行均匀搜索;通过基于网格技术的外部存档非劣解删选策略,有效地保留了逼近Pareto前沿的非劣解;引入一种广义的学习策略来提升粒子向Pareto前沿收敛的概率.实验结...     

Optimal topology design of structures under dynamic loads

When elastic structures are subjected to dynamic loads, a propagation problem is considered to predict structural transient response. To achieve better dynamic performance, it is important to establish an optimum structural design method. Previous work focused on minimizing the structural weight subject to dynamic constraints on displacement, stress, frequency, and member size. Even though these methods made it possible to obtain the optimal size and shape of a structure, it is necessary to obtain an optimal topology for a truly optimal design. In this paper, the homogenization design method is utilized to generate the optimal topology for structures and an explicit direct integration scheme is employed to solve the linear transient problems. The optimization problem is formulated to find the best configuration of structures that minimizes the dynamic compliance within a specified time interval. Examples demonstrate that the homogenization design method can be extended to the optimal topology design method of structures under impact loads.Presented at WCSMO-2, held in Zakopane, Poland, 1997     

Optimum cost design of reinforced concrete slabs using neural dynamics model

For structural optimization algorithms to find widespread usage among practicing engineering they must be formulated as cost optimization and applied to realistic structures subjected to the actual constraints of commonly used design codes such as the ACI code. In this article, a general formulation is presented for cost optimization of single- and multiple-span RC slabs with various end conditions (simply supported, one end continuous, both ends continuous, and cantilever) subjected to all the constraints of the ACI code. The problem is formulated as a mixed integer-discrete variable optimization problem with three design variables: thickness of slab, steel bar diameter, and bar spacing. The solution is obtained in two stages. In the first stage, the neural dynamics model of Adeli and Park is used to obtain an optimum solution assuming continuous variables. Next, the problem is formulated as a mixed integer-discrete optimization problem and solved using a perturbation technique in order to find practical values for the design variables. Practicality, robustness, and excellent convergence properties of the algorithm are demonstrated by application to four examples.     

Optimization of reinforced concrete frames subjected to historical time-history loadings using DMPSO algorithm

In this paper, the seismic design of reinforced concrete (RC) frames subjected to time-history loadings was formulated as an optimization problem. Because finding the optimum design is relatively difficult and time-consuming for structural dynamics problems, an innovative algorithm combining multi-criterion decision-making (DM) and Particle Swarm Optimization (PSO), called DMPSO, was presented for accelerating convergence toward the optimum solution. The effectiveness of the proposed algorithm was illustrated in some benchmark reinforced concrete optimization problems. The main goal was to minimize the cost or weight of structures subjected to time-history loadings while satisfying all design requirements imposed by building design codes. The results confirmed the ability of the proposed algorithm to find the optimal solutions for structural optimization problems subjected to time-history loadings.     

基于色彩案例和灰度关联分析的产品配色设计方法

为有效辅助工业设计师进行产品配色设计,提出基于色彩案例和灰度关联分析的 产品配色设计方法。从目标意象出发,通过分析并筛选产品配色样本,研究色彩合并、取舍和 色彩案例表示方法,基于对目标产品赋色区域划分实现色彩案例向目标产品配色映射,引入灰 度关联分析方法评价映射后的色彩方案与案例色彩的关联性。以剪式升降机的配色设计为例, 验证了该方法能够有效实现案例色彩向目标产品配色转换,生成用户满意方案。     

Topological design considering flexibility under periodic loads

Topology optimization has been extensively considered to design the structural configuration for the stiffness maximization and the eigenfrequency maximization. In this paper, we construct a topology optimization method implementing flexibility with the time-periodic loading condition. First, the flexibility in the dynamic periodic loading is formulated using the mutual energy concept. Second, the multi-optimization problem is formulated using a new multi-objective function in order to obtain an optimal solution incorporating both flexibility and stiffness. Next, the topology optimization procedure is developed using the homogenization design method. Finally, some examples are provided to confirm the optimal design method presented here. Received January 18, 1999     

Sensitivity analysis of optimum solutions by updating active constraints: application in aircraft structural design

Often the parameters considered as constants in an optimization problem have some uncertainty and it is interesting to know how the optimum solution is modified when these values are changed. The only way to continue having the optimal solution is to perform a new optimization loop, but this may require a high computational effort if the optimization problem is large. However, there are several procedures to obtain the new optimal design, based on getting the sensitivities of design variables and objective function with respect to a fixed parameter. Most of these methods require obtaining second derivatives which has a significant computational cost. This paper uses the feasible direction-based technique updating the active constraints to obtain the approximate optimum design. This procedure only requires the first derivatives and it is noted that the updating set of active constraints improves the result, making possible a greater fixed parameter variation. This methodology is applied to an example of very common structural optimization problems in technical literature and to a real aircraft structure.     

基于多学科设计优化的路网交通分布式协同控制

城市路网交通控制直接影响着交通运行效率,对其优化研究已成为缓解城市交通拥堵问题的热点之一.鉴于此,针对高峰交通路网将其分为过饱和区域与过饱和关联区域,在采用灰色关联分析-谱聚类方法对关联区域划分的基础上,构建路网交通分布式协同控制模型,进一步提出基于多学科设计优化的过饱和区域及其关联区域协同优化求解方法.通过搭建实例路网模型分析算法优化效果,结果表明所提出方法能够明显改善路网交通运行效率,有助于缓解城市通勤高峰时段的交通拥堵和扩散问题.     

Efficient optimum seismic design of reinforced concrete frames with nonlinear structural analysis procedures

Performance-based seismic design offers enhanced control of structural damage for different levels of earthquake hazard. Nevertheless, the number of studies dealing with the optimum performance-based seismic design of reinforced concrete frames is rather limited. This observation can be attributed to the need for nonlinear structural analysis procedures to calculate seismic demands. Nonlinear analysis of reinforced concrete frames is accompanied by high computational costs and requires a priori knowledge of steel reinforcement. To address this issue, previous studies on optimum performance-based seismic design of reinforced concrete frames use independent design variables to represent steel reinforcement in the optimization problem. This approach drives to a great number of design variables, which magnifies exponentially the search space undermining the ability of the optimization algorithms to reach the optimum solutions. This study presents a computationally efficient procedure tailored to the optimum performance-based seismic design of reinforced concrete frames. The novel feature of the proposed approach is that it employs a deformation-based, iterative procedure for the design of steel reinforcement of reinforced concrete frames to meet their performance objectives given the cross-sectional dimensions of the structural members. In this manner, only the cross-sectional dimensions of structural members need to be addressed by the optimization algorithms as independent design variables. The developed solution strategy is applied to the optimum seismic design of reinforced concrete frames using pushover and nonlinear response-history analysis and it is found that it outperforms previous solution approaches.