Title :
A New Evolutionary Optimization Algorithm Based on Super-individual
Author :
Wang, Shun-Jiu ; Zhang, Xin-Li ; Ni, Chang-Jian
Author_Institution :
Inst. of Plateau Meteorol., China Meteorol. Adm., Chengdu, China
Abstract :
According to evolutionary principle, a new evolutionary optimization algorithm based on super-individual (SIEA) is presented. In the SIEA, the population is generated based on super-individual, and the complex process in genetic algorithm (GA) is not required. At last, several typical optimization problems including extremum, multivariable and NiH problem are used to test the efficiency of the SIEA. The results show the SIEA has good performance, which can be a new method to solve complicated optimization problems.
Keywords :
genetic algorithms; NiH problem; evolutionary optimization algorithm; extremum problem; genetic algorithm; multivariable problem; super-individual; Educational institutions; Genetic algorithms; Genetic mutations; Information technology; Intelligent systems; Lagrangian functions; Meteorology; Newton method; Optimization methods; Testing; Evolutionary algorithm; genetic algorithm; optimization; super-individual;
Conference_Titel :
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3571-5
DOI :
10.1109/GCIS.2009.181
