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CAINE
2003
14 years 6 days ago
A Genetic Algorithm for Clustering on Very Large Data Sets
Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups h...
Jim Gasvoda, Qin Ding
GECCO
2005
Springer
130views Optimization» more  GECCO 2005»
14 years 4 months ago
Hybrid real-coded mutation for genetic algorithms applied to graph layouts
In this paper we introduce an application of real-coded genetic algorithms to the problem of consistent graph layout and exploring the role of mutation for this particular problem...
Dana Vrajitoru, Jason DeBoni
GECCO
2005
Springer
143views Optimization» more  GECCO 2005»
14 years 4 months ago
Advanced models of cellular genetic algorithms evaluated on SAT
Cellular genetic algorithms (cGAs) are mainly characterized by their spatially decentralized population, in which individuals can only interact with their neighbors. In this work,...
Enrique Alba, Hugo Alfonso, Bernabé Dorrons...
SAC
2000
ACM
14 years 3 months ago
A Weighted Coding in a Genetic Algorithm for the Degree-Constrained Minimum Spanning Tree Problem
The coding by which chromosomes represent candidate solutions is a fundamental design choice in a genetic algorithm. This paper describes a novel coding of spanning trees in a gen...
Günther R. Raidl, Bryant A. Julstrom
GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
14 years 5 months ago
Three interconnected parameters for genetic algorithms
When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...
Pedro A. Diaz-Gomez, Dean F. Hougen