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GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
13 years 7 months ago
Dual-population genetic algorithm for nonstationary optimization
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Taejin Park, Ri Choe, Kwang Ryel Ryu
GECCO
2004
Springer
124views Optimization» more  GECCO 2004»
13 years 11 months ago
A Statistical Model of GA Dynamics for the OneMax Problem
A model of the dynamics of solving the counting-ones (OneMax) problem using a simple genetic algorithm (GA) is developed. It uses statistics of the early generations of GA runs to ...
Bulent Buyukbozkirli, Erik D. Goodman
BIOSYSTEMS
2008
129views more  BIOSYSTEMS 2008»
13 years 6 months ago
Reconstruction of DNA sequences using genetic algorithms and cellular automata: Towards mutation prediction?
Change of DNA sequence that fuels evolution is, to a certain extent, a deterministic process because mutagenesis does not occur in an absolutely random manner. So far, it has not ...
Ch. Mizas, Georgios Ch. Sirakoulis, Vasilios A. Ma...
BMCBI
2010
108views more  BMCBI 2010»
13 years 6 months ago
A genetic ensemble approach for gene-gene interaction identification
Background: It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases...
Pengyi Yang, Joshua W. K. Ho, Albert Y. Zomaya, Bi...
GECCO
2009
Springer
147views Optimization» more  GECCO 2009»
14 years 25 days ago
Evolutionary algorithms and multi-objectivization for the travelling salesman problem
This paper studies the multi-objectivization of single-objective optimization problems (SOOP) using evolutionary multi-objective algorithms (EMOAs). In contrast to the single-obje...
Martin Jähne, Xiaodong Li, Jürgen Branke