The multi-population genetic evolutionary optimization algorithm and its application to mechanical optimization

被引：0

作者：

Luo, Youxin ^{[1
]}

Che, Xiaoyi ^{[1
]}

Xiao, Weiyue ^{[1
]}

机构：

[1] College of Mechanical Engineering, Hunan University of Arts and Science, Changde, 415000, China

来源：

Electronic Journal of Geotechnical Engineering | 2014年 / 19 L卷

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

To overcome the problem of low convergence speed and sensitivity to local convergence with the traditional Genetic Algorithm (GA) to handle complex functions, a novel compound evolutionary algorithm, namely, Multiple Population Genetic Evolutionary Optimization Algorithm (MPGA) , was introduced and selecting parameters are given. MPGA algorithm program was also developed. The computing example of mechanical optimization design shows that this algorithm has no special requirements on the characteristics of optimal designing problems, which has a fairly good universal adaptability and a reliable operation of program with a strong ability of overall convergence and high efficiency. © 2014 ejge.

引用

页码：2605 / 2610

共 50 条

[41] EOS: a Parallel, Self-Adaptive, Multi-Population Evolutionary Algorithm for Constrained Global Optimization [J].

Federici, Lorenzo ;

Benedikter, Boris ;

Zavoli, Alessandro .

2020 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2020,

[42] A simple multi-population evolutionary algorithm using PSO strategy for constrained engineering design optimization [J].

Liu, Yi ;

Mu, Caihong ;

Kou, Weidong ;

Liu, Jing .

International Journal of Digital Content Technology and its Applications, 2012, 6 (13) :532-541

[43] A multi-population evolutionary algorithm based on knowledge transfer for constrained many-objective optimization [J].

Ge, Wenlong ;

Zhang, Shanxin ;

Song, Weida ;

Wang, Wei .

ENGINEERING OPTIMIZATION, 2025, 57 (03) :813-843

[44] BMPGA: A bi-objective multi-population genetic algorithm for multi-modal function optimization [J].

Yao, J ;

Kharma, N ;

Grogono, P .

2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS, 2005, :816-823

[45] A novel three-stage multi-population evolutionary algorithm for constrained multi-objective optimization problems [J].

Shi, Chenli ;

Wang, Ziqi ;

Jin, Xiaohang ;

Xu, Zhengguo ;

Wang, Zhangsheng ;

Shen, Peng .

COMPLEX & INTELLIGENT SYSTEMS, 2024, 10 (01) :655-675

[46] A novel three-stage multi-population evolutionary algorithm for constrained multi-objective optimization problems [J].

Chenli Shi ;

Ziqi Wang ;

Xiaohang Jin ;

Zhengguo Xu ;

Zhangsheng Wang ;

Peng Shen .

Complex & Intelligent Systems, 2024, 10 :655-675

[47] The Novel Compound Evolutionary Optimization Algorithm with Hybrid Discrete Variables and its Application to Mechanical Optimization [J].

Luo, Youxin .

MANUFACTURING SCIENCE AND ENGINEERING, PTS 1-5, 2010, 97-101 :3276-3280

[48] A Genetic Algorithm Based on Multi-bee Population Evolutionary for Numerical Optimization [J].

Lu, Xueyan ;

Zhou, Yongquan .

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, :1294-1298

[49] Coordinate multi-population genetic algorithms for multi-modal function optimization [J].

Li, Min-Qiang ;

Kou, Ji-Song .

Zidonghua Xuebao/Acta Automatica Sinica, 2002, 28 (04) :497-504

[50] An adaptive strategy based multi-population multi-objective optimization algorithm [J].

Zhao, Tianhao ;

Wu, Linjie ;

Cui, Zhihua ;

Qin, A. K. .

INFORMATION SCIENCES, 2025, 686

← 1 2 3 4 5 →