Add to ORKGThis paper presents implementation details of GPU-based genetic algorithm submitted to GPUs for Genetic and Evolutionary Com-putation competition taking place at GECCO’09.
Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly...
V diplomskem delu smo poskusili ugotoviti, kakšne pohitritve lahko dosežemo v izvajanju genetskega a...
This paper proposes a new approach to produce classification rules based on evolutionary computation...
This thesis represents master's thesis focused on acceleration of Genetic algorithms using GPU. Firs...
We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel co...
Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. GAs is one of...
International audienceA parallel solution to the implementation of evolutionary algorithms is propos...
Evolutionary algorithms (EA) are proven effective and robust in searching large varied spaces in a w...
There are many combinatorial optimization problems such as flow shop scheduling, quadraticassignment...
This paper investigates the speed improvements available when using a graphics processing unit (GPU)...
A genetic algorithm (GA) is an optimization method based on natural selection. Genetic algorithms ha...
In this paper, we propose to parallelize a Hybrid Genetic Algorithm (HGA) on Graphics Processing Uni...
Genetic algorithms (GAs) are powerful solutions to optimization problems arising from manufacturing ...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
Genetic algorithms (GAs) are optimization techniques which imitate the way that nature selects the b...
Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly...
V diplomskem delu smo poskusili ugotoviti, kakšne pohitritve lahko dosežemo v izvajanju genetskega a...
This paper proposes a new approach to produce classification rules based on evolutionary computation...
This thesis represents master's thesis focused on acceleration of Genetic algorithms using GPU. Firs...
We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel co...
Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. GAs is one of...
International audienceA parallel solution to the implementation of evolutionary algorithms is propos...
Evolutionary algorithms (EA) are proven effective and robust in searching large varied spaces in a w...
There are many combinatorial optimization problems such as flow shop scheduling, quadraticassignment...
This paper investigates the speed improvements available when using a graphics processing unit (GPU)...
A genetic algorithm (GA) is an optimization method based on natural selection. Genetic algorithms ha...
In this paper, we propose to parallelize a Hybrid Genetic Algorithm (HGA) on Graphics Processing Uni...
Genetic algorithms (GAs) are powerful solutions to optimization problems arising from manufacturing ...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
Genetic algorithms (GAs) are optimization techniques which imitate the way that nature selects the b...
Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly...
V diplomskem delu smo poskusili ugotoviti, kakšne pohitritve lahko dosežemo v izvajanju genetskega a...
This paper proposes a new approach to produce classification rules based on evolutionary computation...