Parallel Genetic Algorithm: Theory & Applications


Stender, J.

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Genetic algorithms in general, and especially parallel genetic algorithm, have been universally considered to be very important in the development of the new generation of IT applications. Genetic algorithms - inspired by the analogy of evolution and population genetics - have demonstrated to be particularly successful in the optimization , classification and control of very-large-scale and varied data. The parallel nature of genetic algorithms suggests parallel processing as the natural route to explore. Parallel genetic algorithms not only provide the basis for tackling problems in a wider range of fields which were previously considered to be virtually unsolvable but also creating a new paradigm within this area and thus establishing a new and promising field of research. This book is intended to provide the reader with an overview of the theoretical, as well as practical aspects involved in the study and implementation of parallel genetic Algorithms. Section two begins by introducing the fundamental theoretical issues which form the basis of parallel genetic algorithms. Section three further develops this knowledge as we consider the current implementational approaches and performance assessment techniques. Section four presents various information on the GAME environment (Genetic Algorithm Manipulation Environment). Section five continues our discussion on a practical level by demonstrating four diverse applications where parallel genetic algorithms are being successfully applied.

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