Title :
A Self-adaptive Genetic Algorithm Based on Region Balance Variation
Author :
Wang, Siyan ; Zhang, Guoli
Author_Institution :
Coll. of Comput. Sci. & Technol., North China Electr. Power Univ., Baoding
Abstract :
Proposing a new algorithm which is simple but effective. Using characteristic of biological evolution and common sense to design the selection operator, improve the variation method of the crossover probability and the mutation probability. Numerical experiments show that the new algorithm is more effective than the comparative algorithm in realizing the high convergence speed, convergence precision, reducing the convergence generation and good at keeping the stability of the adaptive genetic algorithm.
Keywords :
Gray codes; genetic algorithms; probability; biological evolution; common sense; crossover probability; gray code; mutation probability; region balance variation; selection operator; self-adaptive genetic algorithm; variation method; Binary codes; Convergence of numerical methods; Data mining; Educational institutions; Encoding; Genetic algorithms; Genetic mutations; Probability; Reflective binary codes; Stability; adaptive genetic algorithm; crossover; gray code; mutation; selection;
Conference_Titel :
Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on
Conference_Location :
Moscow
Print_ISBN :
978-0-7695-3543-2
DOI :
10.1109/WKDD.2009.167
