"Parallel Evolutionary Computation" focuses on the aspects
related to the parallelization of evolutionary computations, such
as parallel genetic operators, parallel fitness evaluation,
distributed genetic algorithms, and parallel hardware
implementations, as well as on their impact on several
applications.
The book is divided into four parts. The first part deals with a
clear software-like and algorithmic vision on parallel evolutionary
optimizations. The second part is about hardware implementations of
genetic algorithms, a valuable topic which is hard to find in the
present literature. The third part treats the problem of
distributed evolutionary computation and presents three interesting
applications wherein parallel EC new ideas are featured. Finally,
the last part deals with the up-to-date field of parallel particle
swarm optimization to illustrate the intrinsic similarities and
potential extensions to techniques in this domain. The book offers
a wide spectrum of sample works developed in leading research
throughout the world about parallel implementations of efficient
techniques at the heart of computational intelligence. It will be
useful both for beginners and experienced researchers in the field
of computational intelligence.
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