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Optimal design of steel portal frames based on genetic algorithms

CHEN Yue, HU Kai

《结构与土木工程前沿（英文）》 2008年第2卷第4期页码 318-322 doi: 10.1007/s11709-008-0055-1

摘要： As for the optimal design of steel portal frames, due to both the complexity of cross selections of beams and columns and the discreteness of design variables, it is difficult to obtain satisfactory results by traditional optimization. Based on a set of constraints of the Technical Specification for Light-weighted Steel Portal Frames of China, a genetic algorithm (GA) optimization program for portal frames, written in MATLAB code, was proposed in this paper. The graph user interface (GUI) is also developed for this optimal program, so that it can be used much more conveniently. Finally, some examples illustrate the effectiveness and efficiency of the genetic-algorithm-based optimal program.

关键词： satisfactory genetic-algorithm-based Technical Specification algorithm efficiency

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A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system usingenergy filter algorithm

Aeidapu MAHESH, Kanwarjit Singh SANDHU

《能源前沿（英文）》 2020年第14卷第1期页码 139-151 doi: 10.1007/s11708-017-0484-4

摘要： In this paper, the genetic algorithm (GA) is applied to optimize a grid connected solar photovoltaic (PV)-wind-battery hybrid system using a novel energy filter algorithm. The main objective of this paper is to minimize the total cost of the hybrid system, while maintaining its reliability. Along with the reliability constraint, some of the important parameters, such as full utilization of complementary nature of PV and wind systems, fluctuations of power injected into the grid and the battery’s state of charge (SOC), have also been considered for the effective sizing of the hybrid system. A novel energy filter algorithm for smoothing the power injected into the grid has been proposed. To validate the proposed method, a detailed case study has been conducted. The results of the case study for different cases, with and without employing the energy filter algorithm, have been presented to demonstrate the effectiveness of the proposed sizing strategy.

关键词： PV-wind-battery hybrid system size optimization genetic algorithm

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Optimal design of steel skeletal structures using the enhanced genetic algorithm methodology

Tugrul TALASLIOGLU

《结构与土木工程前沿（英文）》 2019年第13卷第4期页码 863-889 doi: 10.1007/s11709-019-0523-9

摘要： This study concerns with the design optimization of steel skeletal structures thereby utilizing both a real-life specification provisions and ready steel profiles named hot-rolled I sections. For this purpose, the enhanced genetic algorithm methodology named EGAwMP is utilized as an optimization tool. The evolutionary search mechanism of EGAwMP is constituted on the basis of generational genetic algorithm (GGA). The exploration capacity of EGAwMP is improved in a way of dividing an entire population into sub-populations and using of a radial basis neural network for dynamically adjustment of EGAwMP’s genetic operator parameters. In order to improve the exploitation capability of EGAwMP, the proposed neural network implementation is also utilized for prediction of more accurate design variables associating with a new design strategy, design codes of which are based on the provisions of LRFD_AISC V3 specification. EGAwMP is applied to determine the real-life ready steel profiles for the optimal design of skeletal structures with 105, 200, 444, and 942 members. EGAwMP accomplishes to increase the quality degrees of optimum designations Furthermore, the importance of using the real-life steel profiles and design codes is also demonstrated. Consequently, EGAwMP is suggested as a design optimization tool for the real-life steel skeletal structures.

关键词： design optimization genetic algorithm multiple populations neural network

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Optimization design of anti-seismic engineering measures for intake tower based on non-dominated sortinggenetic algorithm-II

《结构与土木工程前沿（英文）》页码 1428-1441 doi: 10.1007/s11709-023-0998-2

摘要： High-rise intake towers in high-intensity seismic areas are prone to structural safety problems under vibration. Therefore, effective and low-cost anti-seismic engineering measures must be designed for protection. An intake tower in northwest China was considered the research object, and its natural vibration characteristics and dynamic response were first analyzed using the mode decomposition response spectrum method based on a three-dimensional finite element model. The non-dominated sorting genetic algorithm-II (NSGA-II) was adopted to optimize the anti-seismic scheme combination by comprehensively considering the dynamic tower response and variable project cost. Finally, the rationality of the original intake tower antiseismic design scheme was evaluated according to the obtained optimal solution set, and recommendations for improvement were proposed. The method adopted in this study may provide significant references for designing anti-seismic measures for high-rise structures such as intake towers located in high-intensity earthquake areas.

关键词： intake tower NSGA-II mode decomposition response spectrum method anti-seismic engineering measures optimization design variable project cost

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Optimization of turbine cold-end system based on BP neural network and genetic algorithm

Chang CHEN,Danmei XIE,Yangheng XIONG,Hengliang ZHANG

《能源前沿（英文）》 2014年第8卷第4期页码 459-463 doi: 10.1007/s11708-014-0335-5

摘要： The operation condition of the cold-end system of a steam turbine has a direct impact on the economy and security of the unit as it is an indispensible auxiliary system of the thermal power unit. Many factors influence the cold-end operation of a steam turbine; therefore, the operation mode needs to be optimized. The optimization analysis of a 1000 MW ultra-supercritical (USC) unit, the turbine cold-end system, was performed utilizing the back propagation (BP) neural network method with genetic algorithm (GA) optimization analysis. The optimized condenser pressure under different conditions was obtained, and it turned out that the optimized parameters were of significance to the performance and economic operation of the system.

关键词： optimization turbine cold-end system BP neural network genetic algorithm

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基于蛙跳思想的量子编码遗传算法

许波,彭志平,余建平,柯文德

《中国工程科学》 2014年第16卷第3期页码 108-112

摘要：

量子门旋转相位、变异概率大小的确定，是目前制约量子遗传算法效率的两个主要问题。本文提出一种基于蛙跳思想的量子编码遗传算法（QRGA），该算法采用自适应的方式对量子旋转门旋转角进行调整，并基于模糊逻辑将蛙跳的步长进行量化以指导变异概率调整，保证进化的方向性和提高算法效率，对比实验结果表明算法可以避免陷入局部最优解，并能快速收敛到全局最优解，在运行时间和解的性能上都取得了较好的效果。

关键词：量子编码量子遗传算法蛙跳算法群体智能

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退火-遗传算法寻优及其实现

王英

《中国工程科学》 2008年第10卷第7期页码 57-59

摘要：

分析了遗传算法及退火算法的优缺点，提出用退火算法改进遗传算法局部的最优值搜索效率低问题。退火算法与遗传算法融合后，使算法在寻优结果上更加迅速精确。通过水泥的配比工程实例，与单纯的遗传算法的结果进行对比，说明该方法是有效的。

关键词：遗传算法退火算法遗传算法改进

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基于加速遗传算法的组合证券投资决策

王硕,唐小我,曾勇

《中国工程科学》 2002年第4卷第9期页码 59-62

摘要：

应用加速遗传算法解决组合证券投资决策问题，可以克服传统遗传算法的缺点：对搜索空间（优化变量空间）的大小变化适应能力差，计算量大，易出现早熟收敛，控制参数的设置技术无明确准则指导等，与已有结果相比，对协方差矩阵无正定性要求，目标函数可以推广到规模庞大，提高预测精度等优点。

关键词：加速遗传算法组合证券投资决策

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Optimization of aero-engine pipeline for avoiding vibration based on length adjustment of straight-line

《机械工程前沿（英文）》 2022年第17卷第1期页码 11-11 doi: 10.1007/s11465-021-0667-x

摘要： In the design and troubleshooting of aero-engine pipeline, the vibration reduction of the pipeline system is often achieved by adjusting the hoop layout, provided that the shape of pipeline remains unchanged. However, in reality, the pipeline system with the best antivibration performance may be obtained only by adjusting the pipeline shape. In this paper, a typical spatial pipeline is taken as the research object, the length of straight-line segment is taken as the design variable, and an innovative optimization method of avoiding vibration of aero-engine pipeline is proposed. The relationship between straight-line segment length and parameters that determine the geometric characteristics of the pipeline, such as the position of key reference points, bending angle, and hoop position, are derived in detail. Based on this, the parametric finite element model of the pipeline system is established. Taking the maximum first-order natural frequency of pipeline as the optimization objective and introducing process constraints and vibration avoidance constraints, the optimization model of the pipeline system is established. The genetic algorithm and the golden section algorithm are selected to solve the optimization model, and the relevant solution procedure is described in detail. Finally, two kinds of pipelines with different total lengths are selected to carry out a case study. Based on the analysis of the influence of straight-line segment length on the vibration characteristics of the pipeline system, the optimization methods developed in this paper are demonstrated. Results show that the developed optimization method can obtain the optimal single value or interval of the straight-line segment length while avoiding the excitation frequency. In addition, the optimization efficiency of the golden section algorithm is remarkably higher than that of the genetic algorithm for length optimization of a single straight-line segment.

关键词： length adjustment spatial pipeline aero-engine vibration avoidance optimization genetic algorithm golden section algorithm

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基于神经网络与遗传算法耦合的煤与瓦斯突出区域预测研究

施式亮,伍爱友

《中国工程科学》 2009年第11卷第9期页码 91-96

摘要：

煤与瓦斯突出是煤矿地下开采过程中的一种动力现象，剧烈的动力效应可导致矿井重大的财产损失和人员伤亡，因此，实现煤与瓦斯突出的有效预测对煤炭工业安全生产具有重要意义。文章以煤与瓦斯突出的自然条件及地质构造特征为基础，针对神经网络易陷入局部极小而引起预测指标权值分布不合理的缺陷，提出了基于神经网络和遗传算法耦合的煤与瓦斯突出区域预测模型，并进行了实例验证。研究结果证明了该模型的合理性，对煤矿实现煤与瓦斯突出区域的预测具有较大的指导价值。

关键词：煤与瓦斯突出区域预测神经网络遗传算法突出等值线

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用遗传算法求解供水泵站的效率优化问题

廖莉,林家恒,张承慧

《中国工程科学》 2002年第4卷第9期页码 54-58

摘要：

供水企业向来是城市的用电大户，其用电量主要体现在泵站水泵机组的电耗上。供水泵站的高效运行对节约电能、安全供水具有极为重要的意义。文章对供水泵站的效率优化问题进行了探讨，在提出用指数曲线准确地拟合水泵性能曲线的基础上，建立了供水栗站效率优化问题的数学模型，并设计了相应的遗传算法进行求解，仿真实验结果表明了该算法合理、有效。

关键词：供水泵站数值拟合优化遗传算法

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Hybrid genetic algorithm for bi-objective resource-constrained project scheduling

Fikri KUCUKSAYACIGIL, Gündüz ULUSOY

《工程管理前沿（英文）》 2020年第7卷第3期页码 426-446 doi: 10.1007/s42524-020-0100-x

摘要： In this study, we considered a bi-objective, multi-project, multi-mode resource-constrained project scheduling problem. We adopted three objective pairs as combinations of the net present value (NPV) as a financial performance measure with one of the time-based performance measures, namely, makespan ( ), mean completion time (MCT), and mean flow time (MFT) (i.e., min /max , min /max , and min /max ). We developed a hybrid non-dominated sorting genetic algorithm II (hybrid-NSGA-II) as a solution method by introducing a backward–forward pass (BFP) procedure and an injection procedure into NSGA-II. The BFP was proposed for new population generation and post-processing. Then, an injection procedure was introduced to increase diversity. The BFP and injection procedures led to improved objective functional values. The injection procedure generated a significantly high number of non-dominated solutions, thereby resulting in great diversity. An extensive computational study was performed. Results showed that hybrid-NSGA-II surpassed NSGA-II in terms of the performance metrics hypervolume, maximum spread, and the number of non-dominated solutions. Solutions were obtained for the objective pairs using hybrid-NSGA-II and three different test problem sets with specific properties. Further analysis was performed by employing cash balance, which was another financial performance measure of practical importance. Several managerial insights and extensions for further research were presented.

关键词： backward–forward scheduling hybrid bi-objective genetic algorithm injection procedure maximum cash balance multi-objective multi-project multi-mode resource-constrained project scheduling problem

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Evaluation of a novel Asymmetric Genetic Algorithm to optimize the structural design of 3D regular and

Mohammad Sadegh ES-HAGHI, Aydin SHISHEGARAN, Timon RABCZUK

《结构与土木工程前沿（英文）》 2020年第14卷第5期页码 1110-1130 doi: 10.1007/s11709-020-0643-2

摘要： We propose a new algorithm, named Asymmetric Genetic Algorithm (AGA), for solving optimization problems of steel frames. The AGA consists of a developed penalty function, which helps to find the best generation of the population. The objective function is to minimize the weight of the whole steel structure under the constraint of ultimate loads defined for structural steel buildings by the American Institute of Steel Construction (AISC). Design variables are the cross-sectional areas of elements (beams and columns) that are selected from the sets of side-flange shape steel sections provided by the AISC. The finite element method (FEM) is utilized for analyzing the behavior of steel frames. A 15-storey three-bay steel planar frame is optimized by AGA in this study, which was previously optimized by algorithms such as Particle Swarm Optimization (PSO), Particle Swarm Optimizer with Passive Congregation (PSOPC), Particle Swarm Ant Colony Optimization (HPSACO), Imperialist Competitive Algorithm (ICA), and Charged System Search (CSS). The results of AGA such as total weight of the structure and number of analyses are compared with the results of these algorithms. AGA performs better in comparison to these algorithms with respect to total weight and number of analyses. In addition, five numerical examples are optimized by AGA, Genetic Algorithm (GA), and optimization modules of SAP2000, and the results of them are compared. The results show that AGA can decrease the time of analyses, the number of analyses, and the total weight of the structure. AGA decreases the total weight of regular and irregular steel frame about 11.1% and 26.4% in comparing with the optimized results of SAP2000, respectively.

关键词： optimization steel frame Asymmetric Genetic Algorithm constraints of ultimate load constraints of serviceability limits penalty function

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Improved genetic algorithm and its application to determination of critical slip surface with arbitrary

LI Liang, CHI Shichun, LIN Gao, CHENG Yungming

《结构与土木工程前沿（英文）》 2008年第2卷第2期页码 145-150 doi: 10.1007/s11709-008-0016-8

摘要： In order to overcome the problem of being trapped by the local minima encountered in applying the simple genetic algorithm (GA) to search the critical slip surface of the slope, an improved procedure based on the harmony search algorithm is proposed. In the searching computation, the new solutions are obtained from the whole information of the current generation. The proposed method may be applied to calculate the minimum factors of safety of two complicated soil slopes. Comparison of the results with existing examples given by other authors has shown that the proposed method is feasible for stability analysis of soil slopes.

关键词： information algorithm Comparison generation feasible

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Application of micro-genetic algorithm for calibration of kinetic parameters in HCCI engine combustion

HUANG Haozhong, SU Wanhua

《能源前沿（英文）》 2008年第2卷第1期页码 86-92 doi: 10.1007/s11708-008-0003-8

摘要： The micro-genetic algorithm (?GA) as a highly effective optimization method, is applied to calibrate to a newly developed reduced chemical kinetic model (40 species and 62 reactions) for the homogeneous charge compression ignition (HCCI) combustion of -heptane to improve its autoignition predictions for different engine operating conditions. The seven kinetic parameters of the calibrated model are determined using a combination of the Micro-Genetic Algorithm and the SENKIN program of CHEMKIN chemical kinetics software package. Simulation results show that the autoignition predictions of the calibrated model agree better with those of the detailed chemical kinetic model (544 species and 2 446 reactions) than the original model over the range of equivalence ratios from 0.1–1.3 and temperature from 300–3 000 K. The results of this study have demonstrated that the mGA is an effective tool to facilitate the calibration of a large number of kinetic parameters in a reduced kinetic model.

关键词： homogeneous different combustion autoignition compression