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Theory and Principled Methods for the Design of Metaheuristics

  • Yossi Borenstein
  • Alberto Moraglio

Part of the Natural Computing Series book series (NCS)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Konstantin Klemm, Peter F. Stadler
    Pages 41-61
  3. Olivier Teytaud, Emmanuel Vazquez
    Pages 111-128
  4. Marc Toussaint
    Pages 129-144
  5. Riccardo Poli, Nicholas Freitag McPhee
    Pages 181-204
  6. Thomas Bartz-Beielstein, Mike Preuss
    Pages 205-245
  7. Patrick D. Surry, Nicholas J. Radcliffe
    Pages 247-270

About this book

Introduction

Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex.

 

In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters.

 

With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.

Keywords

Evolutionary algorithms Evolutionary computing Global optimization Heuristics Landscapes Metaheuristics Multiobjective optimization Representations Search algorithms

Editors and affiliations

  • Yossi Borenstein
    • 1
  • Alberto Moraglio
    • 2
  1. 1.VisualDNALondonUnited Kingdom
  2. 2.University of Birmingham School of Computer ScienceBirminghamUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-33206-7
  • Copyright Information Springer-Verlag Berlin Heidelberg 2014
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-33205-0
  • Online ISBN 978-3-642-33206-7
  • Series Print ISSN 1619-7127
  • Buy this book on publisher's site