Parallel Problem Solving from Nature PPSN VI

6th International Conference Paris, France, September 18–20, 2000 Proceedings

  • Marc Schoenauer
  • Kalyanmoy Deb
  • Günther Rudolph
  • Xin Yao
  • Evelyne Lutton
  • Juan Julian Merelo
  • Hans-Paul Schwefel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1917)

Table of contents

  1. Front Matter
    Pages I-XXI
  2. Invited Papers

  3. Analysis and Theory of EAs

    1. Front Matter
      Pages 27-27
    2. Hans-Georg Beyer, Kalyanmoy Deb
      Pages 59-68
    3. Thomas Jansen, Ingo Wegener
      Pages 89-98
    4. Yoshiyuki Matsumura, Kazuhiro Ohkura, Kanji Ueda
      Pages 119-128
    5. Colin R Reeves
      Pages 139-148
    6. Oliver Sharpe
      Pages 149-158

About these proceedings

Introduction

We are proud to introduce the proceedings of the Sixth International Conference on Parallel Problem Solving from Nature, PPSN VI, held in Paris, Prance, on 18-20 September 2000. PPSN VI was organized in association with the Genetic and Evolutionary Computing Conference (GECCO'2000) and the Congress on Evolutionary Computation (CEC'2000), reflecting the beneficial interaction between the conference activities in Europe and in the USA in the field of natural computation. Starting in 1990 in Dortmund, Germany (Proceedings, LNCS vol. 496, Sprin­ ger, 1991), this biannual meeting has been held in Brussels, Belgium (Procee­ dings, Elsevier, 1992), Jerusalem, Israel (Proceedings, LNCS vol. 866, Springer, 1994), Berlin, Germany (Proceedings, LNCS vol. 1141, Springer, 1996), and Amsterdam, The Netherlands (Proceedings, LNCS vol. 1498, Springer, 1998), where it was decided that Paris would be the location of the 2000 conference with Marc Schoenauer as the general chair. The scientific content of the PPSN conference focuses on problem solving pa­ radigms gleaned from a natural models. Characteristic for Natural Computing is the metaphorical use of concepts, principles and mechanisms underlying natural systems, such as evolutionary processes involving mutation, recombination, and selection in natural evolution, annealing or punctuated equilibrium processes of many-particle systems in physics, growth processes in nature and economics, collective intelligence in biology, DNA-based computing in molecular chemistry, and multi-cellular behavioral processes in neural and immune networks.

Keywords

Algorithms algorithm combinatorial optimization evolutionary algorithm genetic programming learning machine learning optimization programming scheduling theory of evolution

Editors and affiliations

  • Marc Schoenauer
    • 1
  • Kalyanmoy Deb
    • 2
  • Günther Rudolph
    • 3
  • Xin Yao
    • 4
  • Evelyne Lutton
    • 5
  • Juan Julian Merelo
    • 6
  • Hans-Paul Schwefel
    • 3
  1. 1.CMAPEcole PolytechniquePalaiseau CedexFrance
  2. 2.Dept. of Mechanical Engineering Kanpur Genetic Algorithms LaboratoryIndian Institute of Technology KanpurKanpur, PinIndia
  3. 3.Fachbereich Informatik, Lehrstuhl für SystemanalyseUniversität DortmundDortmundGermany
  4. 4.School of Computer ScienceThe University of BirminghamEdgbaston, BirminghamUK
  5. 5.Projet FractalesINRIA RocquencourtLe Chesnay CedexFrance
  6. 6.Dept. de Arquitectura y Technologa de los Computadores, GeNeura TeamUniversidad de GranadaGranada

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-45356-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 2000
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-41056-0
  • Online ISBN 978-3-540-45356-7
  • Series Print ISSN 0302-9743