Add to ORKGSome novel parallel schemes of genetic and adaptive partitioned random search algorithms are presented. They are realised on Flosolver-NAL's parallel computer platform using C language. Performance studies and implementation aspects are discussed
Abstract—In this paper an improved adaptive parallel genetic algorithm is proposed to solve problems...
In this paper we develop a study on several types of parallel genetic algorithms (PGAs). Our motivat...
Parallel genetic algorithms (PGAs) have been traditionally used to extend the power of serial geneti...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
AbstractThis paper presents a network parallel genetic algorithm for the one machine sequencing prob...
Parallel genetic algorithms, models and implementations, attempts to exploit the intrinsically paral...
ABSTRACT. Genetic algorithms (GAs) are powerful search techniques that are used success-fully to sol...
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 mo-tiva...
Evolutionary algorithms (EAs) are modern techniques for searching complex spaces for on optimum [11]...
Genetic algorithms, a stochastic evolutionary computing technique, have demonstrated a capacity for ...
Genetic Algorithms (GAs) have been implemented on a number of multiprocessor machines. In many cases...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
Spatial allocation of resource for parallel genetic algorithm is achieved by the partitioning of the...
Abstract—In this paper an improved adaptive parallel genetic algorithm is proposed to solve problems...
In this paper we develop a study on several types of parallel genetic algorithms (PGAs). Our motivat...
Parallel genetic algorithms (PGAs) have been traditionally used to extend the power of serial geneti...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
AbstractThis paper presents a network parallel genetic algorithm for the one machine sequencing prob...
Parallel genetic algorithms, models and implementations, attempts to exploit the intrinsically paral...
ABSTRACT. Genetic algorithms (GAs) are powerful search techniques that are used success-fully to sol...
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 mo-tiva...
Evolutionary algorithms (EAs) are modern techniques for searching complex spaces for on optimum [11]...
Genetic algorithms, a stochastic evolutionary computing technique, have demonstrated a capacity for ...
Genetic Algorithms (GAs) have been implemented on a number of multiprocessor machines. In many cases...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
Spatial allocation of resource for parallel genetic algorithm is achieved by the partitioning of the...
Abstract—In this paper an improved adaptive parallel genetic algorithm is proposed to solve problems...
In this paper we develop a study on several types of parallel genetic algorithms (PGAs). Our motivat...
Parallel genetic algorithms (PGAs) have been traditionally used to extend the power of serial geneti...