Title :
A novel hybrid genetic algorithm for global optimization
Author :
Wang, Shuihua ; Wu, Lenan
Author_Institution :
Sch. of Inf. Sci. & Eng., Southeast Univ., Nanjing, China
Abstract :
In order to propose a more effective function optimization method, a novel algorithm named HGPSA was proposed which integrates the powerful global search ability of GA and the excellent local search ability of PS. The experiments of 10 runs on three test functions (Powell function, Rosenbrock function, and Schaffer function) demonstrate that the proposed algorithm is superior to both GA and PS with respect to the successful rate. Therefore, the proposed algorithm is valid.
Keywords :
genetic algorithms; function optimization; global optimization; hybrid genetic algorithm; local search ability; Computers; Genetic algorithms; Genetics; Microorganisms; Optimization; Search problems; USA Councils; genetic algorithm; global optimization; pattern search;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5582983