Metaheuristics for Dynamic Optimization

  • Enrique Alba
  • Amir Nakib
  • Patrick Siarry

Part of the Studies in Computational Intelligence book series (SCI, volume 433)

Table of contents

  1. Front Matter
    Pages 1-28
  2. Amir Nakib, Patrick Siarry
    Pages 1-16
  3. Briseida Sarasola, Enrique Alba
    Pages 17-33
  4. Irene Moser, Raymond Chiong
    Pages 35-59
  5. Mardé Helbig, Andries P. Engelbrecht
    Pages 147-188
  6. Guillermo Leguizamón, Enrique Alba
    Pages 189-210
  7. Julien Lepagnot, Amir Nakib, Hamouche Oulhadj, Patrick Siarry
    Pages 211-224
  8. Victoria S. Aragón, Susana C. Esquivel, Carlos A. Coello
    Pages 225-263
  9. Mostepha R. Khouadjia, Briseida Sarasola, Enrique Alba, El-Ghazali Talbi, Laetitia Jourdan
    Pages 265-289
  10. Amir Hajjam, Jean-Charles Créput, Abderrafiãa Koukam
    Pages 309-339
  11. Pedro C. Pinto, Thomas A. Runkler, João M. C. Sousa
    Pages 341-369
  12. Back Matter
    Pages 0--1

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.


Computational Intelligence Dynamic Optimization Metaheuristics

Editors and affiliations

  • Enrique Alba
    • 1
  • Amir Nakib
    • 2
  • Patrick Siarry
    • 3
  1. 1., E.T.S.I. Informática (3-2-12)Universidad de MálagaMálagaSpain
  2. 2., LISSIUniversité Paris-Est CréteilCréteilFrance
  3. 3., Laboratoire LiSSiUniversité Paris-Est Créteil Val de MarnCréteilFrance

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-642-30664-8
  • Online ISBN 978-3-642-30665-5
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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