Simplified Genetic Algorithm: Simplify and Improve RGA for Parameter Optimizations

Advances in Electrical and Computer Engineering

NGAMTAWEE, R. ; WARDKEIN, P..

关键词: algorithm;    evolutionary computation;    genetic algorithms;    optimization;    particle swarm optimization;   

DOI  :  10.4316/AECE.2014.04009

学科分类：计算机科学（综合）

来源: Universitatea "Stefan cel Mare" din Suceava

【 摘 要 】

The structural complexity and complicated generic operators of Genetic Algorithm (GA) contribute to its slow computational speed. Furthermore, GA and other similar algorithms with a small population size are vulnerable to the problem of premature convergence. Premature convergence causes the algorithms to stagnate and stop searching, giving rise to wasteful computation. Even though the problem can be addressed with a larger population size, computational time is inevitably increased. This research paper has thus proposed Simplified Genetic Algorithm (SimpGA). This algorithm utilizes a one-pair-built-all structure in which only two parent chromosomes are required to produce the entire population (offspring). Rather than relying on the conventional operators, simplified operators, i.e. timer mutation, diform crossover and topmost selection, are used in the proposed SimpGA. In addition, tests are carried out with SimpGA on four test functions and four applications. The experimental results show that SimpGA is simpler to implement and performs well, especially in a small population environment.

【 授权许可】

Unknown