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Multi-objective genetic algorithms based structural optimization and experimental investigation of the

Pengxing YI,Lijian DONG,Tielin SHI

《机械工程前沿（英文）》 2014年 第9卷 第4期   页码 354-367 doi: 10.1007/s11465-014-0319-5

摘要：

To improve the dynamic performance and reduce the weight of the planet carrier in wind turbine gearbox, a multi-objective optimization method, which is driven by the maximum deformation, the maximum stress and the minimum mass of the studied part, is proposed by combining the response surface method and genetic algorithms in this paper. Firstly, the design points’ distribution for the design variables of the planet carrier is established with the central composite design (CCD) method. Then, based on the computing results of finite element analysis (FEA), the response surface analysis is conducted to find out the proper sets of design variable values. And a multi-objective genetic algorithm (MOGA) is applied to determine the direction of optimization. As well, this method is applied to design and optimize the planet carrier in a 1.5 MW wind turbine gearbox, the results of which are validated by an experimental modal test. Compared with the original design, the mass and the stress of the optimized planet carrier are respectively reduced by 9.3% and 40%. Consequently, the cost of planet carrier is greatly reduced and its stability is also improved.

关键词： planet carrier     multi-objective optimization     genetic algorithms     wind turbine gearbox     modal experiment    

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多目标优化与决策问题的演化算法

谢涛,陈火旺

《中国工程科学》 2002年 第4卷 第2期   页码 59-68

摘要：

近年来，多目标优化与决策问题求解已成为演化计算的一个重要研究方向。为使演化算法的种群解 能尽快收敛并均匀分布于多目标问题的非劣最优域，多目标演化算法的研究热点集中在基于Pareto最优概念的 种群个体的比较与排序、适应值賦值与小生境技术等方面。介绍了多目标优化与决策技术的发展历史与分类方 法，分析了基于Pareto最优概念与不基于Pareto最优概念两大类的多目标演化算法，并详细比较与分析了几种 典型多目标演化算法。其次，论述了与多目标演化算法研究紧密相关的一些问题，如多目标问题解的性质，测 试函数集设计，算法性能评估技术，算法收敛性，并行实现以及实际多目标优化问题的处理等。

关键词： 演化计算     多目标优化与决策     Pareto最优    

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Recent advances in system reliability optimization driven by importance measures

Shubin SI, Jiangbin ZHAO, Zhiqiang CAI, Hongyan DUI

《工程管理前沿（英文）》 2020年 第7卷 第3期   页码 335-358 doi: 10.1007/s42524-020-0112-6

摘要： System reliability optimization problems have been widely discussed to maximize system reliability with resource constraints. Birnbaum importance is a well-known method for evaluating the effect of component reliability on system reliability. Many importance measures (IMs) are extended for binary, multistate, and continuous systems from different aspects based on the Birnbaum importance. Recently, these IMs have been applied in allocating limited resources to the component to maximize system performance. Therefore, the significance of Birnbaum importance is illustrated from the perspective of probability principle and gradient geometrical sense. Furthermore, the equations of various extended IMs are provided subsequently. The rules for simple optimization problems are summarized to enhance system reliability by using ranking or heuristic methods based on IMs. The importance-based optimization algorithms for complex or large-scale systems are generalized to obtain remarkable solutions by using IM-based local search or simplification methods. Furthermore, a general framework driven by IM is developed to solve optimization problems. Finally, some challenges in system reliability optimization that need to be solved in the future are presented.

关键词： importance measure     system performance     reliability optimization     optimization rules     optimization algorithms    

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Crack detection of the cantilever beam using new triple hybrid algorithms based on Particle Swarm Optimization

Amin GHANNADIASL; Saeedeh GHAEMIFARD

《结构与土木工程前沿（英文）》 2022年 第16卷 第9期   页码 1127-1140 doi: 10.1007/s11709-022-0838-9

摘要： The presence of cracks in a concrete structure reduces its performance and increases in the size of cracks result in the failure of the structure. Therefore, the accurate determination of crack characteristics, such as location and depth, is one of the key engineering issues for assessment of the reliability of structures. This paper deals with the inverse analysis of the crack detection problems using triple hybrid algorithms based on Particle Swarm Optimization (PSO); these hybrids are Particle Swarm Optimization-Genetic Algorithm-Firefly Algorithm (PSO-GA-FA), Particle Swarm Optimization-Grey Wolf Optimization-Firefly Algorithm (PSO-GWO-FA), and Particle Swarm Optimization-Genetic Algorithm-Grey Wolf Optimization (PSO-GA-GWO). A strong correlation exists between the changes in the natural frequency of a concrete beam and the crack parameters. Thus, the location and depth of a crack in a beam can be predicted by measuring its natural frequency. Hence, the measured natural frequency can be used as the input parameter of the algorithm. In this paper, this is applied to identify crack location and depth in a cantilever beam using the new hybrid algorithms. The results show that among the proposed triple hybrid algorithms, the PSO-GA-FA and PSO-GWO-FA algorithms are much more effective than PSO-GA-GWO algorithm for the crack detection.

关键词： crack     cantilever beam     triple hybrid algorithms     Particle Swarm Optimization    

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Comparative seismic design optimization of spatial steel dome structures through three recent metaheuristicalgorithms

《结构与土木工程前沿（英文）》 2022年 第16卷 第1期   页码 57-74 doi: 10.1007/s11709-021-0784-y

摘要： Steel dome structures, with their striking structural forms, take a place among the impressive and aesthetic load bearing systems featuring large internal spaces without internal columns. In this paper, the seismic design optimization of spatial steel dome structures is achieved through three recent metaheuristic algorithms that are water strider (WS), grey wolf (GW), and brain storm optimization (BSO). The structural elements of the domes are treated as design variables collected in member groups. The structural stress and stability limitations are enforced by ASD-AISC provisions. Also, the displacement restrictions are considered in design procedure. The metaheuristic algorithms are encoded in MATLAB interacting with SAP2000 for gathering structural reactions through open application programming interface (OAPI). The optimum spatial steel dome designs achieved by proposed WS, GW, and BSO algorithms are compared with respect to solution accuracy, convergence rates, and reliability, utilizing three real-size design examples for considering both the previously reported optimum design results obtained by classical metaheuristic algorithms and a gradient descent-based hyperband optimization (HBO) algorithm.

关键词： steel dome optimization     water strider algorithm     grey wolf algorithm     brain storm optimization algorithm     hyperband optimization algorithm    

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Optimal design of double-layer barrel vaults using genetic and pattern search algorithms and optimized

《结构与土木工程前沿（英文）》 2023年 第17卷 第3期   页码 378-395 doi: 10.1007/s11709-022-0899-9

摘要： This paper presents a combined method based on optimized neural networks and optimization algorithms to solve structural optimization problems. The main idea is to utilize an optimized artificial neural network (OANN) as a surrogate model to reduce the number of computations for structural analysis. First, the OANN is trained appropriately. Subsequently, the main optimization problem is solved using the OANN and a population-based algorithm. The algorithms considered in this step are the arithmetic optimization algorithm (AOA) and genetic algorithm (GA). Finally, the abovementioned problem is solved using the optimal point obtained from the previous step and the pattern search (PS) algorithm. To evaluate the performance of the proposed method, two numerical examples are considered. In the first example, the performance of two algorithms, OANN + AOA + PS and OANN + GA + PS, is investigated. Using the GA reduces the elapsed time by approximately 50% compared with using the AOA. Results show that both the OANN + GA + PS and OANN + AOA + PS algorithms perform well in solving structural optimization problems and achieve the same optimal design. However, the OANN + GA + PS algorithm requires significantly fewer function evaluations to achieve the same accuracy as the OANN + AOA + PS algorithm.

关键词： optimization     surrogate models     artificial neural network     SAP2000     genetic algorithm    

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An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and group

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

《结构与土木工程前沿（英文）》 2020年 第14卷 第4期   页码 907-929 doi: 10.1007/s11709-020-0628-1

摘要： In this study, the performance of an efficient two-stage methodology which is applied in a damage detection system using a surrogate model of the structure has been investigated. In the first stage, in order to locate the damage accurately, the performance of the modal strain energy based index for using different numbers of natural mode shapes has been evaluated using the confusion matrix. In the second stage, to estimate the damage extent, the sensitivity of most used modal properties due to damage, such as natural frequency and flexibility matrix is compared with the mean normalized modal strain energy (MNMSE) of suspected damaged elements. Moreover, a modal property change vector is evaluated using the group method of data handling (GMDH) network as a surrogate model during damage extent estimation by optimization algorithm; in this part of methodology, the performance of the three popular optimization algorithms including particle swarm optimization (PSO), bat algorithm (BA), and colliding bodies optimization (CBO) is examined and in this regard, root mean square deviation ( ) based on the modal property change vector has been proposed as an objective function. Furthermore, the effect of noise in the measurement of structural responses by the sensors has also been studied. Finally, in order to achieve the most generalized neural network as a surrogate model, GMDH performance is compared with a properly trained cascade feed-forward neural network (CFNN) with log-sigmoid hidden layer transfer function. The results indicate that the accuracy of damage extent estimation is acceptable in the case of integration of PSO and MNMSE. Moreover, the GMDH model is also more efficient and mimics the behavior of the structure slightly better than CFNN model.

关键词： two-stage method     modal strain energy     surrogate model     GMDH     optimization damage detection    

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Predicting shear strength of slender beams without reinforcement using hybrid gradient boosting trees and optimizationalgorithms

Thuy-Anh NGUYEN; Hai-Bang LY; Van Quan TRAN

《结构与土木工程前沿（英文）》 2022年 第16卷 第10期   页码 1267-1286 doi: 10.1007/s11709-022-0842-0

摘要： Shear failure of slender reinforced concrete beams without stirrups has surely been a complicated occurrence that has proven challenging to adequately understand. The primary purpose of this work is to develop machine learning models capable of reliably predicting the shear strength of non-shear-reinforced slender beams (SB). A database encompassing 1118 experimental findings from the relevant literature was compiled, containing eight distinct factors. Gradient Boosting (GB) technique was developed and evaluated in combination with three different optimization algorithms, namely Particle Swarm Optimization (PSO), Random Annealing Optimization (RA), and Simulated Annealing Optimization (SA). The findings suggested that GB-SA could deliver strong prediction results and effectively generalizes the connection between the input and output variables. Shap values and two-dimensional PDP analysis were then carried out. Engineers may use the findings in this work to define beam's geometrical components and material used to achieve the desired shear strength of SB without reinforcement.

关键词： slender beam     shear strength     gradient boosting     optimization algorithms    

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Estimation of optimum design of structural systems via machine learning

《结构与土木工程前沿（英文）》 2021年 第15卷 第6期   页码 1441-1452 doi: 10.1007/s11709-021-0774-0

摘要： Three different structural engineering designs were investigated to determine optimum design variables, and then to estimate design parameters and the main objective function of designs directly, speedily, and effectively. Two different optimization operations were carried out: One used the harmony search (HS) algorithm, combining different ranges of both HS parameters and iteration with population numbers. The other used an estimation application that was done via artificial neural networks (ANN) to find out the estimated values of parameters. To explore the estimation success of ANN models, different test cases were proposed for the three structural designs. Outcomes of the study suggest that ANN estimation for structures is an effective, successful, and speedy tool to forecast and determine the real optimum results for any design model.

关键词： optimization     metaheuristic algorithms     harmony search     structural designs     machine learning     artificial neural networks    

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优化算法在所有权保留数据挖掘中的应用 None

Muhammad KAMRAN, Ehsan Ullah MUNIR

《信息与电子工程前沿（英文）》 2018年 第19卷 第2期   页码 151-164 doi: 10.1631/FITEE.1601479

摘要： 从敏感数据中提取知识往往需要协同工作。统计数据库根据这些敏感数据生成，并由各利益相关方共享。在此情况下，共享数据的所有权保护变得尤为重要。水印技术正逐渐成为一种推行数字数据格式所有权的有效工具，但该技术也可能导致数据失真。因此，从具有水印的数据中提取的知识可能不准确。数据失真程度由可用性约束条件来控制，这反过来又限制了可用于添加水印的带宽。尽管大带宽能保证鲁棒性，但可能降低数据质量。该问题可以通过在可用性约束条件下优化可用带宽来解决。如今，优化技术——尤其是生物启发式技术——已成为解决该类问题的首选。本文分析了多种优化方案及其可行性，用于优化添加水印的最大可用带宽，并期望达到以下两个目标：（1）保持数据中存储的知识不变；（2）在可用性约束条件下使可用带宽最大化，以取得最佳鲁棒性。第一个目标利用一个可用性约束模型实现，该模型能确保知识不会因嵌入水印而受到损害。第二个目标通过找到满足第一个目标的可用性约束条件下最大带宽实现。采用不同指标对多种优化方案性能进行了评估。

关键词： 信息安全；优化技术；数字版权；水印技术    

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Analytical algorithms of compressive bending capacity of bolted circumferential joint in metro shield

《结构与土木工程前沿（英文）》   页码 901-914 doi: 10.1007/s11709-023-0915-8

摘要： The integrity and bearing capacity of segment joints in shield tunnels are associated closely with the mechanical properties of the joints. This study focuses on the mechanical characteristics and mechanism of a bolted circumferential joint during the entire bearing process. Simplified analytical algorithms for four stress stages are established to describe the bearing behaviors of the joint under a compressive bending load. A height adjustment coefficient, α, for the outer concrete compression zone is introduced into a simplified analytical model. Factors affecting α are determined, and the degree of influence of these factors is investigated via orthogonal numerical simulations. The numerical results show that α can be specified as approximately 0.2 for most metro shield tunnels in China. Subsequently, a case study is performed to verify the rationality of the simplified theoretical analysis for the segment joint via numerical simulations and experiments. Using the proposed simplified analytical algorithms, a parametric investigation is conducted to discuss the factors affecting the ultimate compressive bending capacity of the joint. The method for optimizing the joint flexural stiffness is clarified. The results of this study can provide a theoretical basis for optimizing the design and prediciting the damage of bolted segment joints in shield tunnels.

关键词： shield tunnel     segment joint     joint structural model     failure mechanism    

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基于遗传算法的工程项目投资综合优化探讨

陈耀明,钟登华,付金强

《中国工程科学》 2006年 第8卷 第7期   页码 68-71

摘要：

利用多目标优化理论、多属性效用函数理论建立了工程建设项目工期、成本和质量的综合均衡优化模型，在网络计划技术的基础上，用遗传算法对模型进行求解，可以得到最满意的决策方案和多个近似满意的备选方案，作为工程建设项目投资综合控制的目标。并应用实例对模型的可行性和实用性进行了验证。

关键词： 工程项目投资     多属性效用函数     遗传算法    

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基于GA-ANFIS在石灰矿技术经济系统中的参数优化研究与应用实践

杨仕教,戴剑勇,曾晟

《中国工程科学》 2005年 第7卷 第6期   页码 61-65

摘要：

为掌握水泥原料矿山系统中的技术经济参数对矿石成本影响的关联规律性，首先运用自适应模糊神经网络对矿山技术经济系统建模，再用并行遗传算法对模型求解，得到了确保矿石成本最小的各项最优技术经济指标，为提高矿山生产管理与经济效益提供了重要的参考价值。

关键词： 自适应模糊神经网络     并行遗传算法     技术经济参数    

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基于遗传算法的单脉冲阵列天线优化

王宏建,高本庆,刘瑞祥

《中国工程科学》 2002年 第4卷 第5期   页码 84-87

摘要：

采用遗传算法来优化单脉冲阵列天线的和、差方向图和方向性系数。在天线阵综合时，若不考虑差方向图和方向性系数的影响，所进行的方向图优化仅仅显示出和方向图的特性，对单脉冲阵列天线追踪目标的精度和作用距离没有保证。而在天线阵综合时兼顾和、差方向图以及方向性系数的优化，既可使得天线能发现目标，并使天线能准确对目标实施准确角跟踪，提髙雷达的跟踪和作战性能。

关键词： 单脉冲阵列天线     遗传算法     方向图     方向性系数    

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Development of surface reconstruction algorithms for optical interferometric measurement

Dongxu WU, Fengzhou FANG

《机械工程前沿（英文）》 2021年 第16卷 第1期   页码 1-31 doi: 10.1007/s11465-020-0602-6

摘要： Optical interferometry is a powerful tool for measuring and characterizing areal surface topography in precision manufacturing. A variety of instruments based on optical interferometry have been developed to meet the measurement needs in various applications, but the existing techniques are simply not enough to meet the ever-increasing requirements in terms of accuracy, speed, robustness, and dynamic range, especially in on-line or on-machine conditions. This paper provides an in-depth perspective of surface topography reconstruction for optical interferometric measurements. Principles, configurations, and applications of typical optical interferometers with different capabilities and limitations are presented. Theoretical background and recent advances of fringe analysis algorithms, including coherence peak sensing and phase-shifting algorithm, are summarized. The new developments in measurement accuracy and repeatability, noise resistance, self-calibration ability, and computational efficiency are discussed. This paper also presents the new challenges that optical interferometry techniques are facing in surface topography measurement. To address these challenges, advanced techniques in image stitching, on-machine measurement, intelligent sampling, parallel computing, and deep learning are explored to improve the functional performance of optical interferometry in future manufacturing metrology.

关键词： surface topography     measurement     optical interferometry     coherence envelope     phase-shifting algorithm    

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标题 作者 时间 类型 操作

Multi-objective genetic algorithms based structural optimization and experimental investigation of the

Pengxing YI,Lijian DONG,Tielin SHI

期刊论文

多目标优化与决策问题的演化算法

谢涛,陈火旺

期刊论文

Recent advances in system reliability optimization driven by importance measures

Shubin SI, Jiangbin ZHAO, Zhiqiang CAI, Hongyan DUI

期刊论文

Crack detection of the cantilever beam using new triple hybrid algorithms based on Particle Swarm Optimization

Amin GHANNADIASL; Saeedeh GHAEMIFARD

期刊论文

Comparative seismic design optimization of spatial steel dome structures through three recent metaheuristicalgorithms

期刊论文

Optimal design of double-layer barrel vaults using genetic and pattern search algorithms and optimized

期刊论文

An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and group

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

期刊论文

Predicting shear strength of slender beams without reinforcement using hybrid gradient boosting trees and optimizationalgorithms

Thuy-Anh NGUYEN; Hai-Bang LY; Van Quan TRAN

期刊论文

Estimation of optimum design of structural systems via machine learning

期刊论文

优化算法在所有权保留数据挖掘中的应用

Muhammad KAMRAN, Ehsan Ullah MUNIR

期刊论文

Analytical algorithms of compressive bending capacity of bolted circumferential joint in metro shield

期刊论文

基于遗传算法的工程项目投资综合优化探讨

陈耀明,钟登华,付金强

期刊论文

基于GA-ANFIS在石灰矿技术经济系统中的参数优化研究与应用实践

杨仕教,戴剑勇,曾晟

期刊论文

基于遗传算法的单脉冲阵列天线优化

王宏建,高本庆,刘瑞祥

期刊论文

Development of surface reconstruction algorithms for optical interferometric measurement

Dongxu WU, Fengzhou FANG

期刊论文