Mining Very Large Databases with Parallel Processing addresses the problem of large-
scale data mining. It is an interdisciplinary text, describing advances in the integration of …

A unified view of metaheuristics This book provides a complete background on
metaheuristics and shows readers how to design and implement efficient algorithms to solve …

Genetic algorithms (GAs) are powerful search techniques that are used successfully to solve
problems in many different disciplines. Parallel GAs are particularly easy to implement and …

This paper contains a modern vision of the parallelization techniques used for evolutionary
algorithms (EAs). The work is motivated by two fundamental facts: 1) the different families of …

As genetic algorithms (GAs) become increasingly popular, they are applied to difficult
problems that may require considerable computations. In such cases, parallel …

In this work we review the most important existing developments and future trends in the
class of Parallel Genetic Algorithms (PGAs). PGAs are mainly subdivided into coarse and …

The use of multiple populations in Genetic Programming is an area that is just beginning to
be investigated. To date a number of conflicting reports have been generated with respect to …

This book is the result of several years of research trying to better characterize parallel
genetic algorithms (pGAs) as a powerful tool for optimization, search, and learning. Readers …

A major problem in the use of genetic algorithms is premature convergence. One approach
for dealing with this problem is the distributed genetic algorithm model. Its basic idea is to …

The field of evolutionary computation (EC) can no longer be considered an esoteric one.
Today, after about thirty years of research, a rich corpus of theory exists and many …