结构优化设计中自适应遗传算法的研究

主要介绍了一种基于非连续设计变量的结构优化设计方法一遗传算法(Genetic Al-gorithms，GA)。首先对遗传算法的来源、基本过程进行了论述；为了提高遗传算法的收敛性能，同时考虑到交叉率和变异率的选取问题，引入一种基于个体适应度值的自适应调整交叉率和变异率的自适应遗传算法，并通过算例表明自适应遗传算法是有效的。     

免疫遗传算法在结构损伤识别中的应用与改进

为了解决结构的多损伤识别问题,提出了基于免疫遗传算法和贝叶斯融合理论的二阶段识别方法。首先将结构的应变能和频率数据作为两种具有互补性质的信息源,通过采用贝叶斯融合理论来初步确定结构的损伤位置,然后通过免疫遗传算法来精确确定结构的损伤位置和程度。考虑到基本免疫遗传算法的搜索效率仍不太高,故提出了疫苗培养、以及双终止条件等改进策略。数值计算结果表明,论文提出的二阶段方法可以有效的识别出结构的损伤位置和程度,而所建议的改进免疫遗传算法明显优于基本免疫遗传算法和简单遗传算法。     

Improving Structural Design by Genetic Search

Design optimization has long been a goal eagerly sought by engineers. The established classic methods of optimization demanded large-scale computing facilities met only by the mainframe computers of the 1960s through 1980s. Two important developments of the last decade have changed the course of events. First, the microcomputer has arrived as a large-capacity, rapid-processing computing capability well up to the needs of optimization. Second, the methods of optimization have been joined by new approaches based on concepts of evolutionary or "genetic" progression in which an initial population (collection) of individuals (designs) is changed progressively in the direction of improved "fitness." The concept of searching a large design space, notionally created by combining all possible values of the design variables and tracing a path through increasingly "better" designs, has become a realistic prospect. The purpose of this paper is to describe the ideas behind the concept of genetic search, to outline the basic principles of the genetic algorithm, to illustrate the genetic algorithm with a simple example of structural optimization, and to consider further developments in this area.     

Modified Genetic Algorithm for the Dynamic Identification of Structural Systems Using Incomplete Measurements

Abstract: A modified real‐coded genetic algorithm to identify the parameters of large structural systems subject to the dynamic loads is presented in this article. The proposed algorithm utilizes several subpopulations and a migration operator with a ring topology is periodically performed to allow the interaction between them. For each subpopulation, a specialized medley of recent genetic operators (crossover and mutation) has been adopted and is briefly discussed. The final algorithm includes a novel operator based on the auto‐adaptive asexual reproduction of the best individual in the current subpopulation. This latter is introduced to avoid a long stagnation at the start of the evolutionary process due to insufficient exploration as well as to attempt an improved local exploration around the current best solution at the end of the search. Moreover, a search space reduction technique is performed to improve, both convergence speed and final accuracy, allowing a genetic‐based search within a reduced region of the initial feasible domain. This numerical technique has been used to identify two shear‐type mechanical systems with 10 and 30 degrees‐of‐freedom, assuming as unknown parameters the mass, the stiffness, and the damping coefficients. The identification will be conducted starting from some noisy acceleration signals to verify, both the computational effectiveness and the accuracy of the proposed optimizer in presence of high noise‐to‐signal ratio. A critical and detailed analysis of the results is presented to investigate the inner work of the optimizer. Finally, its performances are examined and compared to the most recent results documented in the current literature to demonstrate the numerical competitiveness of the proposed strategy.     

Pareto-Optimal Conceptual Design of the Structural Layout of Buildings Using a Multicriteria Genetic Algorithm

This article presents a computational procedure for multicriteria optimal conceptual design of the structural layout of buildings subject to given specifications and requirements. Two objective criteria are considered for evaluating alternative designs. The first objective concerns minimizing the building project cost through minimization of a function defining the combined costs of the building structural system and the land for the building site. The second objective concerns optimizing the flexibility of floor space usage, which is a qualitative criterion that is given a quantitative form through minimization of an exponential function that relates tributary load area to the spacing of columns. A multicriteria genetic algorithm (MGA) is applied to solve the biobjective conceptual building layout design problem using Pareto optimization theory . The MGA process is shown to be similar to that of the simple genetic algorithm, except that the fitness evaluation of candidate designs is based on a distance metric related to the Pareto-optimal set. A variable‐mutation technique is introduced to maintain genetic diversity and to accelerate the stochastic search for the global optimum. An example conceptual building layout design is presented using the MGA, and the applicability and efficiency of the developed computational conceptual design procedure are discussed.     

采用遗传算法对蜗杆-行星减速器进行优化设计

蜗杆-行星减速器的传动比大,适用于低速重载场合,但优化模型复杂。采用遗传算法,以总体积最小为目标函数,建立了优化设计的数学模型,得到全局最优点。以某履带行走装置为例进行优化,得到合理的设计方案。     

Fuzzy Control of Base-Isolation System Using Multi-Objective Genetic Algorithm

Abstract:   In this study, a friction pendulum system (FPS) and a magnetorheological (MR) damper are employed as the isolator and supplemental damping device, respectively, of a smart base-isolation system. Neuro-fuzzy models are used to represent dynamic behavior of the MR damper and FPS. A fuzzy logic controller (FLC) is used to modulate the MR damper so as to minimize structural acceleration while maintaining acceptable base displacement levels. To this end, a multi-objective optimization scheme that uses a nondominated multi-objective genetic algorithm (NSGA-II) is used to optimize parameters of membership functions and find appropriate fuzzy rules. To demonstrate the effectiveness of the proposed multi-objective genetic algorithm for FLC, a numerical study of a smart base-isolation system is conducted using several historical earthquakes. It is shown that the proposed method can find optimal fuzzy rules and that the NSGA-II-optimized FLC outperforms not only a passive control strategy but also a human-designed FLC and a conventional semiactive control algorithm.     

用遗传算法实现污水管网的优化设计

提出用遗传算法优化大中型污水管网的设计,并与节点递归算法相结合,既满足了污水管网系统内部节点的水力衔接,也保证了管网系统的全局优化。遗传算法具有只需目标函数值而无需导数等信息的优点,并能从全局出发对管网水力参数进行优化,达到费用最低的目标。结合中型污水管网的优化设计,确定了遗传算法的运行参数。     

多层连体的高层建筑结构设计

珠海供电局电力生产调度综合楼地上21层,总高91.1 m.主楼为框架—剪力墙结构体系,为多层连体的结构形式.连接体部分的框架梁及与之相连的框架柱采用型钢混凝土构件,这加强了关键构件的安全性及整体结构的延性.详细分析了多层连体结构的动力特性和在中震、大震作用下的连接体楼板应力,同时进行了弹性和弹塑性时程分析.从分析结果中可以看出,在地震作用下顶部连接体的楼板应力较大,中下部连接体的楼板应力较小.     

Structural Analysis with Fuzzy Variables

Abstract: The analysis of existing structures requires engineers to model two types of uncertainty, cognitive and non-cognitive. The objective of this paper is to reexamine structural analysis methods by considering the cognitive type of uncertainty. Two analytical approaches are proposed for this purpose: (1) combining the displacement method with fuzzy arithmetic and (2) considering all possible permutations of extreme values of any uncertain variables in a structure using the displacement method. The first approach, which is based on fuzzy arithmetic, requires less computing time as compared with the permutations method but only obtains approximate solutions. However, the second approach produces the exact solution. For the purpose of illustration, the modulus of elasticity E is assumed to be an uncertain variable and is modeled as a triangular fuzzy number. The structural behavior was investigated due to this cognitive uncertainty in E. The results based on the second approach show that if E is a triangular fuzzy number, the member forces can be either fuzzy numbers or crisp values, depending on the structural type. In addition, modified definitions for fuzzy division and fuzzy subtraction are proposed in this paper. Applications of these modified definitions and proposed methods are also presented.     

粒子群优化算法在结构参数识别中的应用

利用PSO算法将系统识别问题转化为高维多模优化问题,进行结构参数识别的研究。PSO算法是一种新颖的随机搜索进化算法,通过采取全局优化的策略确保算法得到优化问题的最优解。在输入输出数据不完备且含真实的噪声污染,以及系统质量、刚度等先验信息又缺乏的情况下,利用将基于该算法的识别方法应用于一个真实结构,验证基于PSO算法的识别方法在真实结构系统识别中的有效性。     

Preliminary Design of Long-Span King-Post Truss Systems with a Genetic Algorithm

This article presents an efficient design approach for the preliminary design of long-span king-post steel truss systems. First of all, the key parameters that govern effectiveness of the design of a truss system that has its own unique geometric configuration are identified. An optimization model based on the identified key design parameters and the proposed simplified analysis model is established next. A genetic algorithm is then applied to search for the optimal key design parameters. Finally, design examples based on the study of two arena projects in North America are presented. The results of the study suggest that the proposed design method provides an efficient and practical solution for the design of long-span king-post truss systems.     

遗传算法定制设计高卸型装载机工作装置

为了拓宽装载机的用途,满足特殊工况下的卸高要求,在普通标准型产品的基础上,定制设计了ZLSO高卸型装载机工作装置。为了降低成本,提高产品中零部件的通用性,只对六连杆机构中个别杆件的参数进行了变动,其他参数保持不变。采用遗传算法作为优化方法,对高卸型装载机工作装置的性能和结构参数进行优化设计。结果表明,定制设计的装载机工作装置符合设计要求。     

Multiple People Picking Assignment and Routing Optimization Based on Genetic Algorithm

In order to improve the picking efficiency,reduce the picking time,this paper take artificial picking operation of a certain distribution center which has double-area warehouse as the studying object.Discuss the picking task allocation and routing problems.Establish the TSP model of order-picking system.Create a heuristic algorithm bases on the Genetic Algorithm(GA)which help to solve the task allocating problem and to get the associated order-picking routes.And achieve the simulation experiment with the Visual 6.0C++platform to prove the rationality of the model and the effectiveness of the arithmetic.     

用优体克隆+子体优生遗传算法识别含水层参数

为识别含水层参数 ,本文在十进制简单遗传算法 (SGA)的基础上 ,提出了一种改进的组合方法 ,即优体克隆 +子体优生遗传算法 (BCC YGCD GA)。理想模型计算表明 ,与SGA比较 ,BCC YGCD GA具有收敛速度快 ,稳定性好的优点 ,是一种值得在实际中推广应用的含水层参数识别方法     

工程实用的遗传算法结构优化设计

针对工程结构设计的特点以及目前遗传算法在大规模设计变量设计中的计算量大、优化结果较差的特点,提出了相应的改进措施,算例表明改进方法是有效的。     

遗传算法在污水管网优化设计中的应用

首先阐述了遗传算法原理,然后对遗传算法在平面布置给定条件下的污水管网优化设计中的应用进行了案例分析,结果表明在程序运行到第11代时已得出优化方案,整个程序运行时间为2．875s。经过优化设计后,污水管网的总造价明显降低。     

改进多种群遗传算法在墙土系统损伤识别中的应用

针对墙土系统损伤识别方法进行研究,提出了一种基于改进多种群遗传算法的墙土系统损伤识别方法。首先,建立了墙土系统动测简化模型,同时对土体发生损伤时墙土系统的特征方程进行理论分析,基于系统的特征方程构造目标函数;其次,对多种群遗传算法进行改进,改进的内容主要包括采用实数编码、采用自适应交叉概率、采用自适应变异概率;最后,利用改进多种群遗传算法分别进行了无噪声条件和噪声条件下的墙土系统损伤定位和定量研究。通过分析结果表明：无论对单处损伤还是多处损伤、单一损伤程度还是多损伤程度,按所提出的方法都能较好的识别出损伤位置和损伤程度,具有较强的抗噪声能力。因此,所提出的方法为墙土系统的损伤识别提供一种简单有效的途径。     

基于遗传算法的单向调压塔尺寸优化研究

介绍了单向调压塔水锤防护的工作原理及计算模型,对单向调压塔水锤防护效果的主要影响因素进行了分析。采用反问题分析方法,以单向调压塔直径、有效水深、补水管直径及水泵出口阀的关闭参数作为决策变量,以单向调压塔的容积最小作为目标函数,建立了单向调压塔尺寸和水泵出口阀关闭程序同时优化的数学模型,并采用改进遗传算法对优化模型进行求解。该优化模型和优化方法在实际工程中的应用表明,数值模拟结果较准确,由此确定的防护措施可靠。