机构:
Tianjin Polytech Univ, Sch Elect Engn & Automat, Tianjin, Peoples R ChinaTianjin Polytech Univ, Sch Elect Engn & Automat, Tianjin, Peoples R China
Xiu Chunbo
[1
]
Lu Lifen
论文数: 0引用数: 0
h-index: 0
机构:
Tianjin Polytech Univ, Sch Elect Engn & Automat, Tianjin, Peoples R ChinaTianjin Polytech Univ, Sch Elect Engn & Automat, Tianjin, Peoples R China
Lu Lifen
[1
]
Cheng Yi
论文数: 0引用数: 0
h-index: 0
机构:
Tianjin Polytech Univ, Sch Elect Engn & Automat, Tianjin, Peoples R ChinaTianjin Polytech Univ, Sch Elect Engn & Automat, Tianjin, Peoples R China
Cheng Yi
[1
]
机构:
[1] Tianjin Polytech Univ, Sch Elect Engn & Automat, Tianjin, Peoples R China
来源:
ADVANCED MEASUREMENT AND TEST, PARTS 1 AND 2
|
2010年
/
439-440卷
关键词:
genetic algorithm;
chaos optimization;
hybrid;
function optimization;
D O I:
10.4028/www.scientific.net/KEM.439-440.641
中图分类号:
TM [电工技术];
TN [电子技术、通信技术];
学科分类号:
0808 ;
0809 ;
摘要:
A hybrid genetic algorithm is proposed based on chaos optimization. The optimization process can be divided into two stages every iteration, one is genetic coarse searching and the other is chaos elaborate searching. Genetic algorithm searches the global solutions in the origin space. An elaborate space near the center of superior individuals is divided from the origin space, which is searched by chaos optimization adequately to generate new better superior individuals for genetic operation. The elaborate space can be compressed quickly to accelerate searching rate and enhance the searching efficiency. In this way, the algorithm has global searching ability and fast convergence rate. The simulation results prove that the algorithm can give satisfied results to function optimization problems.