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GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
15 years 11 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...
CEC
2005
IEEE
15 years 9 months ago
Heterogeneous multiprocessor scheduling with differential evolution
The problem of scheduling a parallel program given by a Directed Acyclic Graph (DAG) of tasks is a well-studied area. We present a new approach which employs Differential Evolution...
Krzysztof Rzadca, Franciszek Seredynski
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 11 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
PAKDD
2009
ACM
123views Data Mining» more  PAKDD 2009»
15 years 12 months ago
Clustering with Lower Bound on Similarity
We propose a new method, called SimClus, for clustering with lower bound on similarity. Instead of accepting k the number of clusters to find, the alternative similarity-based app...
Mohammad Al Hasan, Saeed Salem, Benjarath Pupacdi,...