Title :
An improved fast-convergent genetic algorithm
Author_Institution :
Wuhan Polytech. Univ., China
Abstract :
As an effective global search method, genetic algorithm has been used in many engineering problems. When it is used in engineering, its slow convergence and poor stability have become the main problems. In order to overcome these problems, from the creation of the initial population, genetic operators, et al., an improved fast-convergent genetic algorithm is proposed. Through the simulation experiments of some hard-optimizing functions, the proposed algorithm shows its faster convergence and better stability than some existing algorithms´.
Keywords :
genetic algorithms; numerical stability; search problems; convergence; fast convergent genetic algorithm; genetic operators; global search method; stability; Computational modeling; Computer science; Convergence; Electronic mail; Genetic algorithms; Genetic engineering; Genetic mutations; Search methods; Stability; Stochastic processes;
Conference_Titel :
Robotics, Intelligent Systems and Signal Processing, 2003. Proceedings. 2003 IEEE International Conference on
Print_ISBN :
0-7803-7925-X
DOI :
10.1109/RISSP.2003.1285761