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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    

Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

《机械工程前沿(英文)》 2006年 第1卷 第3期   页码 313-316 doi: 10.1007/s11465-006-0026-y

摘要: It is a very important task to automatically fix the number of die in the image recognition system of a fully automatic die bonder. A multiobjective image recognition algorithm based on clustering Genetic Algorithm (GA), is proposed in this paper. In the evolutionary process of GA, a clustering method is provided that utilizes information from the template and the fitness landscape of the current population. The whole population is grouped into different niches by the clustering method. Experimental results demonstrated that the number of target images could be determined by the algorithm automatically, and multiple targets could be recognized at a time. As a result, time consumed by one image recognition is shortened, the performance of the image recognition system is improved, and the atomization of the system is fulfilled.

关键词: clustering     different     recognition algorithm     Algorithm     multiobjective    

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

《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    

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    

背包问题的混合粒子群优化算法

高尚,杨静宇

《中国工程科学》 2006年 第8卷 第11期   页码 94-98

摘要:

经典的粒子群是一个有效的寻找连续函数极值的方法,结合遗传算法的思想提出的混合粒子群算法来解决背包问题,经过比较测试,6种混合粒子群算法的效果都比较好,特别交叉策略A和变异策略C的混合粒子群算法是最好的且简单有效的算法,并成功地运用在投资问题中。对于目前还没有好的解法的组合优化问题,很容易地修改此算法就可解决。

关键词: 粒子群算法     背包问题     遗传算法     变异    

Control algorithm of a servo platform

Shouyong XIE, Xiwen LI, Shuzi YANG, Mingjin YANG,

《机械工程前沿(英文)》 2010年 第5卷 第3期   页码 353-355 doi: 10.1007/s11465-010-0098-6

摘要: According to the characteristics of the movement of a special-purpose three-axis servo platform, this paper presents an improved grey prediction proportional integral derivative (PID) control algorithm. Different weights at different time are given to different sampling moments in the algorithm, and the time meanings of the sample data are paid more attention. Simulation results show that the performance of response and stability of the platform of the improved algorithm is better than that of the traditional one. The control algorithm meets all requirements of the control system of the special-purpose three-axis servo platform.

关键词: grey prediction     proportional integral derivative (PID) control     improved algorithm     weight     servo platform    

Predictor-corrector algorithm for solving quasi-separated-flow and transient distributed-parameter model

Ping ZHANG, Guoliang DING

《能源前沿(英文)》 2010年 第4卷 第4期   页码 535-541 doi: 10.1007/s11708-010-0113-y

摘要: The successive sub?stitution (SS) method is a suitable approach to solving the transient distributed-parameter model for heat exchangers. However, this method must be enhanced because its convergence heavily depends on the iterative initial pressure. When the iterative initial pressure is improperly assigned, the calculated flow rates become negative values, causing the state parameters to exhibit negative values as well. Therefore, a predictor-corrector algorithm (PCA) is proposed to improve the convergence of the SS method. A predictor is developed to determine an appropriate iterative initial pressure. Total fluid mass is adopted as the convergence criterion of pressure iteration instead of outlet flow rate as is done in the SS method. Convergence analysis and case study of the PCA and SS method are conducted, which show that the PCA has better convergence than the SS method under the same working conditions.

关键词: algorithm     convergence     heat exchanger     modeling     transient    

Implementation of an optimum algorithm for structural reliability analysis based on FEM

CHENG Ying, TU Hong-mao, FAN Hong-li

《机械工程前沿(英文)》 2006年 第1卷 第4期   页码 468-471 doi: 10.1007/s11465-006-0061-8

摘要: To analyze structural reliability by the stochastic FE (finite element) method rapidly and efficiently, a method combined with the FE method and gradient optimum algorithm based on ANSYS was presented when referring to the geometric interpretation of structural reliability index. ANSYS-based development was adopted to implement it. Results of an example demonstrate that the method requires fewer FE calculations compared with the design point method and Monte-Carlo simulation, and achieves satisfactory accuracy.

关键词: satisfactory     interpretation     algorithm     structural reliability     stochastic FE    

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    

Compressive strength prediction and optimization design of sustainable concrete based on squirrel search algorithm-extreme

《结构与土木工程前沿(英文)》   页码 1310-1325 doi: 10.1007/s11709-023-0997-3

摘要: Concrete is the most commonly used construction material. However, its production leads to high carbon dioxide (CO2) emissions and energy consumption. Therefore, developing waste-substitutable concrete components is necessary. Improving the sustainability and greenness of concrete is the focus of this research. In this regard, 899 data points were collected from existing studies where cement, slag, fly ash, superplasticizer, coarse aggregate, and fine aggregate were considered potential influential factors. The complex relationship between influential factors and concrete compressive strength makes the prediction and estimation of compressive strength difficult. Instead of the traditional compressive strength test, this study combines five novel metaheuristic algorithms with extreme gradient boosting (XGB) to predict the compressive strength of green concrete based on fly ash and blast furnace slag. The intelligent prediction models were assessed using the root mean square error (RMSE), coefficient of determination (R2), mean absolute error (MAE), and variance accounted for (VAF). The results indicated that the squirrel search algorithm-extreme gradient boosting (SSA-XGB) yielded the best overall prediction performance with R2 values of 0.9930 and 0.9576, VAF values of 99.30 and 95.79, MAE values of 0.52 and 2.50, RMSE of 1.34 and 3.31 for the training and testing sets, respectively. The remaining five prediction methods yield promising results. Therefore, the developed hybrid XGB model can be introduced as an accurate and fast technique for the performance prediction of green concrete. Finally, the developed SSA-XGB considered the effects of all the input factors on the compressive strength. The ability of the model to predict the performance of concrete with unknown proportions can play a significant role in accelerating the development and application of sustainable concrete and furthering a sustainable economy.

关键词: sustainable concrete     fly ash     slay     extreme gradient boosting technique     squirrel search algorithm     parametric analysis    

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    

Estimation of distribution algorithm enhanced particle swarm optimization for water distribution network

Xuewei QI,Ke LI,Walter D. POTTER

《环境科学与工程前沿(英文)》 2016年 第10卷 第2期   页码 341-351 doi: 10.1007/s11783-015-0776-z

摘要: The optimization of a water distribution network (WDN) is a highly nonlinear, multi-modal, and constrained combinatorial problem. Particle swarm optimization (PSO) has been shown to be a fast converging algorithm for WDN optimization. An improved estimation of distribution algorithm (EDA) using historic best positions to construct a sample space is hybridized with PSO both in sequential and in parallel to improve population diversity control and avoid premature convergence. Two water distribution network benchmark examples from the literature are adopted to evaluate the performance of the proposed hybrid algorithms. The experimental results indicate that the proposed algorithms achieved the literature record minimum (6.081 M$) for the small size Hanoi network. For the large size Balerma network, the parallel hybrid achieved a slightly lower minimum (1.921M?) than the current literature reported best minimum (1.923M?). The average number of evaluations needed to achieve the minimum is one order smaller than most existing algorithms. With a fixed, small number of evaluations, the sequential hybrid outperforms the parallel hybrid showing its capability for fast convergence. The fitness and diversity of the populations were tracked for the proposed algorithms. The track record suggests that constructing an EDA sample space with historic best positions can improve diversity control significantly. Parallel hybridization also helps to improve diversity control yet its effect is relatively less significant.

关键词: particle swarm optimization (PSO)     diversity control     estimation of distribution algorithm (EDA)     water distribution network (WDN)     premature convergence     hybrid strategy    

Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing

Reza TEIMOURI, Hamed SOHRABPOOR

《机械工程前沿(英文)》 2013年 第8卷 第4期   页码 429-442 doi: 10.1007/s11465-013-0277-3

摘要:

Electrochemical machining process (ECM) is increasing its importance due to some of the specific advantages which can be exploited during machining operation. The process offers several special privileges such as higher machining rate, better accuracy and control, and wider range of materials that can be machined. Contribution of too many predominate parameters in the process, makes its prediction and selection of optimal values really complex, especially while the process is programmized for machining of hard materials. In the present work in order to investigate effects of electrolyte concentration, electrolyte flow rate, applied voltage and feed rate on material removal rate (MRR) and surface roughness (SR) the adaptive neuro-fuzzy inference systems (ANFIS) have been used for creation predictive models based on experimental observations. Then the ANFIS 3D surfaces have been plotted for analyzing effects of process parameters on MRR and SR. Finally, the cuckoo optimization algorithm (COA) was used for selection solutions in which the process reaches maximum material removal rate and minimum surface roughness simultaneously. Results indicated that the ANFIS technique has superiority in modeling of MRR and SR with high prediction accuracy. Also, results obtained while applying of COA have been compared with those derived from confirmatory experiments which validate the applicability and suitability of the proposed techniques in enhancing the performance of ECM process.

关键词: electrochemical machining process (ECM)     modeling     adaptive neuro-fuzzy inference system (ANFIS)     optimization     cuckoo optimization algorithm (COA)    

A rank-based multiple-choice secretary algorithm for minimising microgrid operating cost under uncertainties

《能源前沿(英文)》 2023年 第17卷 第2期   页码 198-210 doi: 10.1007/s11708-023-0874-8

摘要: The increasing use of distributed energy resources changes the way to manage the electricity system. Unlike the traditional centralized powered utility, many homes and businesses with local electricity generators have established their own microgrids, which increases the use of renewable energy while introducing a new challenge to the management of the microgrid system from the mismatch and unknown of renewable energy generations, load demands, and dynamic electricity prices. To address this challenge, a rank-based multiple-choice secretary algorithm (RMSA) was proposed for microgrid management, to reduce the microgrid operating cost. Rather than relying on the complete information of future dynamic variables or accurate predictive approaches, a lightweight solution was used to make real-time decisions under uncertainties. The RMSA enables a microgrid to reduce the operating cost by determining the best electricity purchase timing for each task under dynamic pricing. Extensive experiments were conducted on real-world data sets to prove the efficacy of our solution in complex and divergent real-world scenarios.

关键词: energy management systems     demand response     scheduling under uncertainty     renewable energy sources     multiple-choice secretary algorithm    

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    

标题 作者 时间 类型 操作

退火-遗传算法寻优及其实现

王英

期刊论文

Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

期刊论文

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

期刊论文

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

Tugrul TALASLIOGLU

期刊论文

背包问题的混合粒子群优化算法

高尚,杨静宇

期刊论文

Control algorithm of a servo platform

Shouyong XIE, Xiwen LI, Shuzi YANG, Mingjin YANG,

期刊论文

Predictor-corrector algorithm for solving quasi-separated-flow and transient distributed-parameter model

Ping ZHANG, Guoliang DING

期刊论文

Implementation of an optimum algorithm for structural reliability analysis based on FEM

CHENG Ying, TU Hong-mao, FAN Hong-li

期刊论文

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

Aeidapu MAHESH, Kanwarjit Singh SANDHU

期刊论文

Compressive strength prediction and optimization design of sustainable concrete based on squirrel search algorithm-extreme

期刊论文

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

期刊论文

Estimation of distribution algorithm enhanced particle swarm optimization for water distribution network

Xuewei QI,Ke LI,Walter D. POTTER

期刊论文

Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing

Reza TEIMOURI, Hamed SOHRABPOOR

期刊论文

A rank-based multiple-choice secretary algorithm for minimising microgrid operating cost under uncertainties

期刊论文

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

LI Liang, CHI Shichun, LIN Gao, CHENG Yungming

期刊论文