Add to ORKGThis paper describes the implementation of a standard genetic algorithm (GA) on the MIMD multiprocessor system NERV. It discusses the special features of the NERV hardware which can be utilized for an efficient implementation of a GA without changing the structure of the algorithm
A genetic algorithm (GA) is an optimization method based on natural selection. Genetic algorithms ha...
Many optimization problems have complex search space, which either increase the solving problem time...
Genetic algorithms (GAs) are used to solve search and optimization problems in which an optimal solu...
This paper describes the implementation of a standard genetic algorithm (GA) on the MIMD multiproces...
Genetic Algorithms (GAs) have been implemented on a number of multiprocessor machines. In many cases...
Numerical experiments were conducted to find out the extent to which a Genetic Algorithm (GA) may be...
AbstractThis paper presents a network parallel genetic algorithm for the one machine sequencing prob...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
Summarization: This paper presents the implementation of a Genetic Algorithm on a XUPV2P platform wi...
Parallel genetic algorithms, models and implementations, attempts to exploit the intrinsically paral...
This paper presents an implementation of three Genetic Algorithm models for solving a reliability op...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
The field of FPGA design is ever-growing due to costs being lower than that of ASICs, as well as the...
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration origin...
A genetic algorithm (GA) is an optimization method based on natural selection. Genetic algorithms ha...
Many optimization problems have complex search space, which either increase the solving problem time...
Genetic algorithms (GAs) are used to solve search and optimization problems in which an optimal solu...
This paper describes the implementation of a standard genetic algorithm (GA) on the MIMD multiproces...
Genetic Algorithms (GAs) have been implemented on a number of multiprocessor machines. In many cases...
Numerical experiments were conducted to find out the extent to which a Genetic Algorithm (GA) may be...
AbstractThis paper presents a network parallel genetic algorithm for the one machine sequencing prob...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
Summarization: This paper presents the implementation of a Genetic Algorithm on a XUPV2P platform wi...
Parallel genetic algorithms, models and implementations, attempts to exploit the intrinsically paral...
This paper presents an implementation of three Genetic Algorithm models for solving a reliability op...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
The field of FPGA design is ever-growing due to costs being lower than that of ASICs, as well as the...
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration origin...
A genetic algorithm (GA) is an optimization method based on natural selection. Genetic algorithms ha...
Many optimization problems have complex search space, which either increase the solving problem time...
Genetic algorithms (GAs) are used to solve search and optimization problems in which an optimal solu...