Add to ORKGThe PgaFrame offers to non-expert users the possibility to solve optimization problems via genetic algorithms on parallel computers. This frame has appeared as the natural fusion of two different projects: PgaPack and Frames. The PgaFrame combines the major features of these projects: it integrates the capabilities to specify genetic algorithms offered by the PgaPack library and the support of Frames to the easy and portable programming of parallel machines. In this way, a complex framework to develop genetic algorithms is achieved
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration origin...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
The PgaFrame offers to non-expert users the possibility to solve optimization problems via genetic a...
The PgaFrame offers to non-expert users the possibility to solve optimization problems via genetic a...
DraftThe PgaFrame ---a frame for parallel genetic algorithms--- offers to non-experts the possibilit...
DraftThe PgaFrame ---a frame for parallel genetic algorithms--- offers to non-experts the possibilit...
PGAPack is a parallel genetic algorithm library that is intended to provide most capabilities desire...
© 2014 Technical University of Munich (TUM).Parallel genetic algorithms (pGAs) are a variant of gene...
PGAPack is the first widely distributed parallel genetic algorithm library. Since its release, sever...
Many optimization problems have complex search space, which either increase the solving problem time...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration origin...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
The PgaFrame offers to non-expert users the possibility to solve optimization problems via genetic a...
The PgaFrame offers to non-expert users the possibility to solve optimization problems via genetic a...
DraftThe PgaFrame ---a frame for parallel genetic algorithms--- offers to non-experts the possibilit...
DraftThe PgaFrame ---a frame for parallel genetic algorithms--- offers to non-experts the possibilit...
PGAPack is a parallel genetic algorithm library that is intended to provide most capabilities desire...
© 2014 Technical University of Munich (TUM).Parallel genetic algorithms (pGAs) are a variant of gene...
PGAPack is the first widely distributed parallel genetic algorithm library. Since its release, sever...
Many optimization problems have complex search space, which either increase the solving problem time...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration origin...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...