Parallel Genetic Algorithms

Book Name:	Parallel Genetic Algorithms
Category:	Algorithms
Free Download:	Available

Parallel Genetic Algorithms

Book Description:

This book is the result of years of research aimed at better describing parallel genetic algorithms (pGA) as a powerful tool for optimization, research, and learning. Readers can learn to solve complex tasks by reducing their high computation time. Dealing with the two fields of science (parallel and AG) is always difficult, and the book seeks to gracefully introduce basic concepts to advanced topics.

The presentation is structured into three parts. The first is to focus on the algorithms themselves, discussing their components, physical parallelism, and best practices for using and evaluating them. The second part deals with the theory of pGA, with questions ranging from theory to practice. The final third section provides a very broad study of pGAs as practical problem solvers, addressing areas such as natural language processing, circuit design, scheduling, and genomics.

This volume will be useful to both researchers and practitioners. The first part introduces pGAs for beginners and advanced researchers looking for a unified view of two areas: GAs and parallelism. The second part partially addresses (and also opens up) new avenues of investigation in pGA theory. The third part is independently accessible to readers interested in the application. The result is an excellent source of information on the modern state and future development of parallel GAs.

Front Matter….Pages –
Front Matter….Pages 1-1
Introduction….Pages 3-13
Parallel Models for Genetic Algorithms….Pages 15-30
Best Practices in Reporting Results with Parallel Genetic Algorithms….Pages 31-51
Front Matter….Pages 53-53
Theoretical Models of Selection Pressure for Distributed GAs….Pages 55-71
Front Matter….Pages 73-73
Natural Language Tagging with Parallel Genetic Algorithms….Pages 75-89
Design of Combinational Logic Circuits….Pages 91-114
Parallel Genetic Algorithm for the Workforce Planning Problem….Pages 115-134
Parallel GAs in Bioinformatics: Assembling DNA Fragments….Pages 135-147
Back Matter….Pages