An Adaptive Genetic Algorithm Based on Population Diversity Strategy

Authors:
Chen Lin
Affiliations:
-
Venue:
WGEC '09 Proceedings of the 2009 Third International Conference on Genetic and Evolutionary Computing
Year:
2009

Citing 0
Cited 2

A population diversity-oriented gene expression programming for function finding

SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
A controlled migration genetic algorithm operator for hardware-in-the-loop experimentation

Engineering Applications of Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Genetic Algorithms are adaptive methods which may be used to solve search and optimization problems. Three basic operations in Genetic Algorithms are selection, crossover and mutation, an important problem using Genetic Algorithms is the premature convergence in local optimum. This paper presents an adaptive genetic algorithm which adjusts probability of mutation dynamicly based on average square deviation of population fitness value that shows the population diversity to solve premature problem. Compared Analysis shows the proposed adaptive Genetic Algorithm is efficient to avoid premature.