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Studies in Computational Intelligence

Metaheuristics for Dynamic Optimization

Editors: Alba, Enrique, Nakib, Amir, Siarry, Patrick (Eds.)

  • Recent research on Metaheuristics for Dynamic Optimization 
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About this book

This book is an updated effort in summarizing the trending topics and new hot research lines in solving dynamic problems using metaheuristics. An analysis of the present state in solving complex problems quickly draws a clear picture: problems that change in time, having noise and uncertainties in their definition are becoming
very important. The tools to face these problems are still to be built, since existing techniques are either slow or inefficient in tracking the many global optima that those problems are presenting to the solver technique.

Thus, this book is devoted to include several of the most important advances in solving dynamic problems. Metaheuristics are the more popular tools to this end, and then we can find in the book how to best use genetic algorithms, particle swarm, ant colonies, immune systems, variable neighborhood search, and many other bioinspired
techniques. Also, neural network solutions are considered in this book.

Both, theory and practice have been addressed in the chapters of the book. Mathematical background and methodological tools in solving this new class of problems and applications are included. From the applications point of view, not just academic benchmarks are dealt with, but also real world applications in logistics and bioinformatics
are discussed here. The book then covers theory and practice, as well as discrete versus continuous dynamic optimization, in the aim of creating a fresh and comprehensive volume. This book is targeted to either beginners and experienced practitioners in dynamic  optimization, since we took care of devising the chapters in a way that a wide audience could profit from its contents. We hope to offer a single source for up-to-date information in dynamic optimization, an inspiring and attractive new research domain that appeared in these last years and is here to stay.

Table of contents (16 chapters)

  • Performance Analysis of Dynamic Optimization Algorithms

    Nakib, Amir (et al.)

    Pages 1-16

  • Quantitative Performance Measures for Dynamic Optimization Problems

    Sarasola, Briseida (et al.)

    Pages 17-33

  • Dynamic Function Optimization: The Moving Peaks Benchmark

    Moser, Irene (et al.)

    Pages 35-59

  • SRCS: A Technique for Comparing Multiple Algorithms under Several Factors in Dynamic Optimization Problems

    Amo, Ignacio G. (et al.)

    Pages 61-77

  • Dynamic Combinatorial Optimization Problems: A Fitness Landscape Analysis

    Rohlfshagen, Philipp (et al.)

    Pages 79-97

Buy this book

eBook $129.00
price for USA in USD (gross)
  • ISBN 978-3-642-30665-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $249.99
price for USA in USD
  • ISBN 978-3-642-30664-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $169.99
price for USA in USD
  • ISBN 978-3-642-44370-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the eBook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Metaheuristics for Dynamic Optimization
Editors
  • Enrique Alba
  • Amir Nakib
  • Patrick Siarry
Series Title
Studies in Computational Intelligence
Series Volume
433
Copyright
2013
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-30665-5
DOI
10.1007/978-3-642-30665-5
Hardcover ISBN
978-3-642-30664-8
Softcover ISBN
978-3-642-44370-1
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XXXI, 398
Topics