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» Introduction to genetic algorithms
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CEC
2008
IEEE
16 years 28 days ago
A study on constrained MA using GA and SQP: Analytical vs. finite-difference gradients
— Many deterministic algorithms in the context of constrained optimization require the first-order derivatives, or the gradient vectors, of the objective and constraint function...
Stephanus Daniel Handoko, Chee Keong Kwoh, Yew-Soo...
GECCO
2007
Springer
276views Optimization» more  GECCO 2007»
16 years 19 days ago
Automatic mutation test input data generation via ant colony
Fault-based testing is often advocated to overcome limitations of other testing approaches; however it is also recognized as being expensive. On the other hand, evolutionary algor...
Kamel Ayari, Salah Bouktif, Giuliano Antoniol
WABI
2007
Springer
110views Bioinformatics» more  WABI 2007»
16 years 17 days ago
Haplotype Inference Via Hierarchical Genotype Parsing
The within-species genetic variation due to recombinations leads to a mosaic-like structure of DNA. This structure can be modeled, e.g. by parsing sample sequences of current DNA w...
Pasi Rastas, Esko Ukkonen
GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
15 years 12 months ago
A multi-objective evolutionary approach to peptide structure redesign and stabilization
The prediction of the native structures of proteins, the socalled protein folding problem, is a NP hard multi-minima optimization problem for which to date no routine solutions ex...
Tim Hohm, Daniel Hoffmann
GECCO
2005
Springer
142views Optimization» more  GECCO 2005»
15 years 12 months ago
Toward evolved flight
We present the first hardware-in-the-loop evolutionary optimization on an ornithopter. Our experiments demonstrate the feasibility of evolving flight through genetic algorithms an...
Rusty Hunt, Gregory Hornby, Jason D. Lohn