AbstractThis paper presents a network parallel genetic algorithm for the one machine sequencing problem. It examines a parallel genetic algorithm in which processors exchange their best solution found at periodic intervals and the case when no exchange is performed. The network parallel genetic algorithm is executed on a cluster of IBM RS/6000 workstations using a master-slave approach. Performance to a serial genetic algorithm is reported
The main aim of this thesis is the comparison of parallel and sequential algorithm implementation fo...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
Parallel implementations of genetic algorithms (GAs) are common, and, in most cases, they succeed to...
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...
Genetic Algorithms (GAs) have been implemented on a number of multiprocessor machines. In many cases...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
Genetic algorithms, a stochastic evolutionary computing technique, have demonstrated a capacity for ...
ABSTRACT. Genetic algorithms (GAs) are powerful search techniques that are used success-fully to sol...
153 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.Parallel implementations of g...
Some novel parallel schemes of genetic and adaptive partitioned random search algorithms are present...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
This paper proposes that a parallel implementa-tion of the genetic algorithm (GA) on the Internet wi...
This paper presents a genetic algorithm solution for the parallel machine scheduling problems with a...
The main aim of this thesis is the comparison of parallel and sequential algorithm implementation fo...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
Parallel implementations of genetic algorithms (GAs) are common, and, in most cases, they succeed to...
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...
Genetic Algorithms (GAs) have been implemented on a number of multiprocessor machines. In many cases...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
Genetic algorithms, a stochastic evolutionary computing technique, have demonstrated a capacity for ...
ABSTRACT. Genetic algorithms (GAs) are powerful search techniques that are used success-fully to sol...
153 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.Parallel implementations of g...
Some novel parallel schemes of genetic and adaptive partitioned random search algorithms are present...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
This paper proposes that a parallel implementa-tion of the genetic algorithm (GA) on the Internet wi...
This paper presents a genetic algorithm solution for the parallel machine scheduling problems with a...
The main aim of this thesis is the comparison of parallel and sequential algorithm implementation fo...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
Parallel implementations of genetic algorithms (GAs) are common, and, in most cases, they succeed to...