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» A Grid-Oriented Genetic Algorithm
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CEC
2005
IEEE
15 years 6 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 9 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...
198
Voted
FOGA
2011
14 years 8 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
CEC
2009
IEEE
15 years 2 months ago
Optimisation of the Beer Distribution Game with complex customer demand patterns
This paper examines a simulation of the Beer Distribution Game and a number of optimisation approaches to this game. This well known game was developed at MIT in the 1960s and has ...
Hongliang Liu, Enda Howley, Jim Duggan
166
Voted
EVOW
2009
Springer
15 years 2 months ago
Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks
Abstract. Evolutionary algorithms such as genetic programming and grammatical evolution have been used for simultaneously optimizing network architecture, variable selection, and w...
Stephen D. Turner, Marylyn D. Ritchie, William S. ...