Application of the Improved PSO-Based Extended Domain Method in Engineering

被引:1
|
作者
Bai, Bin [1 ,2 ]
Guo, Zhi-wei [3 ]
Wu, Qi-liang [4 ]
Zhang, Junyi [1 ,2 ]
Cui, Yan-chao [5 ]
机构
[1] Hebei Univ Technol, State Key Lab Reliabil & Intelligence Elect Equip, Tianjin 300401, Peoples R China
[2] Hebei Univ Technol, Sch Mech Engn, Tianjin 300401, Peoples R China
[3] Shenyang Engine Res Inst, Shenyang 110015, Peoples R China
[4] Tiangong Univ, Sch Elect Engn & Automat, Tianjin 300387, Peoples R China
[5] AVIC Tianjin Aviat Elect Co Ltd, Tianjin 300308, Peoples R China
基金
中国国家自然科学基金;
关键词
PARTICLE SWARM OPTIMIZATION; DESIGN; ALGORITHM;
D O I
10.1155/2020/2846181
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The standard particle swarm optimization (PSO) algorithm is the boundary constraints of simple variables, which can hardly be directly applied in the constrained optimization. Furthermore, the standard PSO algorithm often fails to obtain the global optimal solution when the dimensionality is high for unconstrained optimization. Thus, an improved PSO-based extended domain method (IPSO-EDM) is proposed to solve engineering optimization problems. The core idea of this method is that the original feasible region is expanded in the constrained optimization which is transformed into the unconstrained optimization by combining the ergodicity of chaos optimization and the evolutionary variation to realize global search. In addition, to verify the effectiveness of the IPSO-EDM, an unconstrained optimization case study, four constrained optimization case studies, and one engineering example are investigated. The results indicate that the computational accuracy of the IPSO-EDM is comparable to that provided by the existing literature, and the computational efficiency of the IPSO-EDM is significantly improved. Meanwhile, this method has conspicuous global search ability and stability in engineering optimization.
引用
收藏
页数:14
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