Traditional Genetic Algorithms (GA) use crossover and mutation as the main genetic operators to achieve population diversity. Previous work using a biologically inspired genetic o...
In this paper, a bottom-up hierarchical genetic algorithm is proposed to visualize clustered data into a planar graph. To achieve global optimization by accelerating local optimiz...
Different kinds of genetic algorithms have been investigated for a parameter identification of a fermentation process. Altogether eight realizations of genetic algorithms have been...
Clustering algorithms are employed in many bioinformatics tasks, including categorization of protein sequences and analysis of gene-expression data. Although these algorithms are r...
In this paper we describe a method for improving genetic-algorithm-based optimization using informed genetic operators. The idea is to make the genetic operators such as mutation ...