Add to ORKGParallel genetic algorithms, models and implementations, attempts to exploit the intrinsically parallel nature of genetic algorithms. By distributing the total population, these models ref1ects a bebaviour nearer to that of natural systems. A variety of parallel computer systems architectures can offer distinct support features for their implementation. Ibis paper shows sorne remarkable characteristics of parallel genetic algorithms, details of a feasible design and their implementation. A1so some results related to the island model are shown.Eje: Redes Neuronales. Algoritmos genéticosRed de Universidades con Carreras en Informática (RedUNCI
The recent development of the Genetic and Evolutionary Computation field lead to a kaleidoscope of a...
This paper presents an implementation of three Genetic Algorithm models for solving a reliability op...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
In this paper we develop a study on several types of parallel genetic algorithms (PGAs). Our mo-tiva...
Migration of individuals allows a fruitful interaction between subpopulations in the island model, a...
Migration of individuals allows a fruitful interaction between subpopulations in the island model, a...
AbstractThis paper presents a network parallel genetic algorithm for the one machine sequencing prob...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
In this paper we develop a study on several types of parallel genetic algorithms (PGAs). Our motivat...
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...
ABSTRACT. Genetic algorithms (GAs) are powerful search techniques that are used success-fully to sol...
Although solutions to many problems can be found using direct analytical methods such as those calcu...
Lecture #1: From Evolution Theory to Evolutionary Computation. Evolutionary computation is a subfiel...
Mathematica has proven itself to be a suitable platform on which to develop prototype Genetic Progr...
The recent development of the Genetic and Evolutionary Computation field lead to a kaleidoscope of a...
This paper presents an implementation of three Genetic Algorithm models for solving a reliability op...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
In this paper we develop a study on several types of parallel genetic algorithms (PGAs). Our mo-tiva...
Migration of individuals allows a fruitful interaction between subpopulations in the island model, a...
Migration of individuals allows a fruitful interaction between subpopulations in the island model, a...
AbstractThis paper presents a network parallel genetic algorithm for the one machine sequencing prob...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
In this paper we develop a study on several types of parallel genetic algorithms (PGAs). Our motivat...
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...
ABSTRACT. Genetic algorithms (GAs) are powerful search techniques that are used success-fully to sol...
Although solutions to many problems can be found using direct analytical methods such as those calcu...
Lecture #1: From Evolution Theory to Evolutionary Computation. Evolutionary computation is a subfiel...
Mathematica has proven itself to be a suitable platform on which to develop prototype Genetic Progr...
The recent development of the Genetic and Evolutionary Computation field lead to a kaleidoscope of a...
This paper presents an implementation of three Genetic Algorithm models for solving a reliability op...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...