EVOLVE- A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation

  • Emilia Tantar
  • Alexandru-Adrian Tantar
  • Pascal Bouvry
  • Pierre Del Moral
  • Pierrick Legrand
  • Carlos A. Coello Coello
  • Oliver Schütze

Part of the Studies in Computational Intelligence book series (SCI, volume 447)

Table of contents

  1. Front Matter
    Pages 1-20
  2. Foundations, Probability and Evolutionary Computation

    1. Front Matter
      Pages 1-1
    2. Pierre Del Moral, Alexandru-Adrian Tantar, Emilia Tantar
      Pages 3-89
    3. Rogelio Salinas-Gutiérrez, Arturo Hernández-Aguirre, Enrique R. Villa-Diharce
      Pages 91-121
    4. Ignacio Segovia Domínguez, Arturo Hernández Aguirre, Enrique Villa Diharce
      Pages 123-153
  3. Set Oriented Numerics

    1. Front Matter
      Pages 155-155
    2. Michael T. M. Emmerich, André H. Deutz, Johannes W. Kruisselbrink
      Pages 157-185
    3. Oliver Schütze, Katrin Witting, Sina Ober-Blöbaum, Michael Dellnitz
      Pages 187-219
  4. Landscape, Coevolution and Cooperation

    1. Front Matter
      Pages 221-221
    2. Marco Tomassini, Fabio Daolio
      Pages 223-245
    3. Olivier Barrière, Evelyne Lutton, Pierre-Henri Wuillemin, Cédric Baudrit, Mariette Sicard, Nathalie Perrot
      Pages 247-287
    4. E. Alba, A. Villagra
      Pages 289-302
  5. Multi-objective Optimization, Heuristic Conversion Algorithms

    1. Front Matter
      Pages 303-303
    2. Adriana Lara, Oliver Schütze, Carlos A. Coello Coello
      Pages 305-332
    3. Christian Grimme, Markus Kemmerling, Joachim Lepping
      Pages 333-363

About this book


The aim of this book is to provide a strong theoretical support for understanding and analyzing the behavior of evolutionary algorithms, as well as for creating a bridge between probability, set-oriented numerics and evolutionary computation.

The volume encloses a collection of contributions that were presented at the EVOLVE 2011 international workshop, held in Luxembourg, May 25-27, 2011, coming from invited speakers and also from selected regular submissions. The aim of EVOLVE is to unify the perspectives offered by probability, set oriented numerics and evolutionary computation. EVOLVE focuses on challenging aspects that arise at the passage from theory to new paradigms and practice, elaborating on the foundations of evolutionary algorithms and theory-inspired methods merged with cutting-edge techniques that ensure performance guarantee factors. EVOLVE is also intended to foster a growing interest for robust and efficient methods with a sound theoretical background.

The chapters enclose challenging theoretical findings, concrete optimization problems as well as new perspectives. By gathering contributions from researchers with different backgrounds, the book is expected to set the basis for a unified view and vocabulary where theoretical advancements may echo in different domains.


Computational Intelligence Evolutionary Computation Probability Set Oriented Numerics

Editors and affiliations

  • Emilia Tantar
    • 1
  • Alexandru-Adrian Tantar
    • 2
  • Pascal Bouvry
    • 3
  • Pierre Del Moral
    • 4
  • Pierrick Legrand
    • 5
  • Carlos A. Coello Coello
    • 6
  • Oliver Schütze
    • 7
  1. 1.Computer Science and Communications, Research UnitUniversity of LuxembourgLuxembourgLuxembourg
  2. 2., Computer Science and CommunicationsUniversity of LuxembourgLuxembourgLuxembourg
  3. 3.Computer Science, and CommunicationsUniversity of LuxembourgLuxembourgLuxembourg
  4. 4.Bordeaux Mathematical Institute, INRIA Bordeaux-Sud OuestUniversité Bordeaux ITalence CedexFrance
  5. 5.Bâtiment Leyteire, UFR Sciences et ModélisationUniversité Bordeaux IIBordeauxFrance
  6. 6., Computer Science DepartmentCINVESTAV-IPNMexico CityMexico
  7. 7., Computer Science DepartmentCINVESTAV-IPNMexico CityMexico

Bibliographic information

  • DOI
  • Copyright Information Springer Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-32725-4
  • Online ISBN 978-3-642-32726-1
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site