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GECCO
2005
Springer
142views Optimization» more  GECCO 2005»
16 years 9 days ago
Choreogenetics: the generation of choreographic variants through genetic mutations and selection
In this paper, a genetic algorithm is introduced to generate variants of a choreographic sequence, which are then selected using different criteria. The mutation phase of the algo...
François-Joseph Lapointe
197
Voted
DSD
2003
IEEE
100views Hardware» more  DSD 2003»
16 years 2 days ago
Fast Heuristics for the Edge Coloring of Large Graphs
Heuristic algorithms for coloring the edges of large undirected single-edge graphs with (or very close to) the minimal number of colors are presented. Compared to simulated anneal...
Mario Hilgemeier, Nicole Drechsler, Rolf Drechsler
GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
15 years 10 months ago
A comparative study of evolutionary optimization techniques in dynamic environments
Genetic Algorithms have widely been used for solving optimization problems in stationary environments. In recent years, there has been a growing interest for investigating and imp...
Demet Ayvaz, Haluk Topcuoglu, Fikret S. Gürge...
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
15 years 11 months ago
Forecasting the MagnetoEncephaloGram (MEG) of Epileptic Patients Using Genetically Optimized Neural Networks
In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients were analyzed using a hybrid neural networks training algorithm. This algorithm combines genetic algorithm...
Adam V. Adamopoulos, Efstratios F. Georgopoulos, S...
FOGA
2011
14 years 10 months ago
Computational complexity analysis of simple genetic programming on two problems modeling isolated program semantics
Analyzing the computational complexity of evolutionary algorithms (EAs) for binary search spaces has significantly informed our understanding of EAs in general. With this paper, ...
Greg Durrett, Frank Neumann, Una-May O'Reilly