PGAPack is a parallel genetic algorithm library that is intended to provide most capabilities desired in a genetic algorithm package, in an integrated, seamless, and portable manner. Key features of PGAPack are as follows: Ability to be called from Fortran or C. Executable on uniprocessors, multiprocessors, multicomputers, and workstation networks. Binary-, integer-, real-, and character-valued native data types. Object-oriented data structure neutral design. Parameterized population replacement. Multiple choices for selection, crossover, and mutation operators. Easy integration of hill-climbing heuristics. Easy-to-use interface for novice and application users. Multiple levels of access for expert users. Full extensibility to support custo...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. Thi...
A software for the implementation of parallel genetic algorithms is presented in this article. The u...
PGAPack is the first widely distributed parallel genetic algorithm library. Since its release, sever...
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...
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...
© 2014 Technical University of Munich (TUM).Parallel genetic algorithms (pGAs) are a variant of gene...
Many optimization problems have complex search space, which either increase the solving problem time...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
A software for the implementation of parallel genetic algorithms is presented in this article. The u...
Parallel genetic algorithms (PGA) use two major modifications compared to the genetic algorithm. Fir...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. Thi...
A software for the implementation of parallel genetic algorithms is presented in this article. The u...
PGAPack is the first widely distributed parallel genetic algorithm library. Since its release, sever...
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...
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...
© 2014 Technical University of Munich (TUM).Parallel genetic algorithms (pGAs) are a variant of gene...
Many optimization problems have complex search space, which either increase the solving problem time...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
A software for the implementation of parallel genetic algorithms is presented in this article. The u...
Parallel genetic algorithms (PGA) use two major modifications compared to the genetic algorithm. Fir...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. Thi...
A software for the implementation of parallel genetic algorithms is presented in this article. The u...