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GECCO
2000
Springer
101views Optimization» more  GECCO 2000»
15 years 3 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
15 years 2 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
14 years 9 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
15 years 6 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»
15 years 3 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