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GECCO
2000
Springer
101views Optimization» more  GECCO 2000»
13 years 11 months ago
Using Genetic Algorithms with Asexual Transposition
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...
Anabela Simões, Ernesto Costa
AAAI
2008
13 years 10 months ago
Visualization of Large-Scale Weighted Clustered Graph: A Genetic Approach
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...
Jiayu Zhou, Youfang Lin, Xi Wang
NMA
2010
13 years 5 months ago
Genetic Algorithms Based Parameter Identification of Yeast Fed-Batch Cultivation
Different kinds of genetic algorithms have been investigated for a parameter identification of a fermentation process. Altogether eight realizations of genetic algorithms have been...
Maria Angelova, Stoyan Tzonkov, Tania Pencheva
ISBRA
2007
Springer
14 years 2 months ago
Clustering Algorithms Optimizer: A Framework for Large Datasets
Clustering algorithms are employed in many bioinformatics tasks, including categorization of protein sequences and analysis of gene-expression data. Although these algorithms are r...
Roy Varshavsky, David Horn, Michal Linial
GECCO
2000
Springer
121views Optimization» more  GECCO 2000»
13 years 11 months ago
Informed operators: Speeding up genetic-algorithm-based design optimization using reduced models
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 ...
Khaled Rasheed, Haym Hirsh