| In this paper the Breeder Genetic Algorithms are compared against both serial and parallel Genetic Algorithms by using a wide range of optimisation functions taken from the literature. The aim is to investigate how the change of the tness function innuences their problem{ solving capabilities. The experimental ndings show that the Breeder Genetic Algorithms outperform the Genetic Algorithms c...

This paper presents the Anisotropic selection scheme for cellular Genetic Algorithms (cGA). This new scheme allows to enhance diversity and to control the selective pressure which are two important issues in Genetic Algorithms, especially when trying to solve difficult optimization problems. Varying the anisotropic degree of selection allows swapping from a cellular to an island model of parall...

ÐTask scheduling is essential for the proper functioning of parallel processor systems. Scheduling of tasks onto networks of parallel processors is an interesting problem that is well-defined and documented in the literature. However, most of the available techniques are based on heuristics that solve certain instances of the scheduling problem very efficiently and in reasonable amounts of time...

Genetic algorithms have been applied to solve the 2-page drawing problem successfully, but they work with one global population, so the search time and space are limited. Parallelization provides an attractive prospect in improving the efficiency and solution quality of genetic algorithms. One of the most popular tools for parallel computing is Message Passing Interface (MPI). In this paper, we...

The Genetic Algorithms draw a similarity from the Genetic mutation and Cross Over within populations from biology. The genetic algorithms are highly parallel in nature. These can be used to solve many important problems like Graph Partitioning, Travelling salesman problems, 0-1 Integer linear programming problem etc. When these are implemented, there exists a trade-off between Genetic search qu...

this paper considers the job scheduling problem in virtual manufacturing cells (vmcs) with the goal of minimizing two objectives namely, makespan and total travelling distance. to solve this problem two algorithms are proposed: traditional non-dominated sorting genetic algorithm (nsga-ii) and knowledge-based non-dominated sorting genetic algorithm (kbnsga-ii). the difference between these algor...

Algorithmic skeleton has received attention as an efficient method of parallel programming in recent years. Using the method, the programmer can implement parallel programs easily. In this study, a set of efficient algorithmic skeletons is introduced for use in implementing parallel genetic algorithm (PGA).A performance modelis derived for each skeleton that makes the comparison of skeletons po...