Parallel Genetic Algorithms: Theory and Real World Applications

✍ Scribed by Gabriel Luque, Enrique Alba (auth.)

Publisher: Springer-Verlag Berlin Heidelberg
Year: 2011
Tongue: English
Leaves: 172
Series: Studies in Computational Intelligence 367
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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 can learn how to solve complex tasks by reducing their high computational times. Dealing with two scientific fields (parallelism and GAs) is always difficult, and the book seeks at gracefully introducing from basic concepts to advanced topics.

The presentation is structured in three parts. The first one is targeted to the algorithms themselves, discussing their components, the physical parallelism, and best practices in using and evaluating them. A second part deals with the theory for pGAs, with an eye on theory-to-practice issues. A final third part offers a very wide study of pGAs as practical problem solvers, addressing domains such as natural language processing, circuits design, scheduling, and genomics.

This volume will be helpful both for researchers and practitioners. The first part shows pGAs to either beginners and mature researchers looking for a unified view of the two fields: GAs and parallelism. The second part partially solves (and also opens) new investigation lines in theory of pGAs. The third part can be accessed independently for readers interested in applications. The result is an excellent source of information on the state of the art and future developments in parallel GAs.

✦ Table of Contents

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 -

✦ Subjects

Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics)

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