Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Parallel Problem Solving from Nature

1st Workshop, PPSN I Dortmund, FRG, October 1-3, 1990. Proceedings

  • Conference proceedings
  • © 1991

Overview

Editors:
  1. Hans-Paul Schwefel
    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Reinhard Männer
    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 496)

Included in the following conference series:

Conference proceedings info: PPSN 1990.

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

About this book

With the appearance of massively parallel computers, increased attention has been paid to algorithms which rely upon analogies to natural processes. This development defines the scope of the PPSN conference at Dortmund in 1990 whose proceedings are presented in this volume. The subjects treated include: - Darwinian methods such as evolution strategies and genetic algorithms; - Boltzmann methods such as simulated annealing; - Classifier systems and neural networks; - Transfer of natural metaphors to artificial problem solving. The main objectives of the conference were: - To gather theoretical results about and experimental comparisons between these algorithms, - To discuss various implementations on different parallel computer architectures, - To summarize the state of the art in the field, which was previously scattered widely both among disciplines and geographically.

Keywords

Table of contents (65 papers)

  1. Front Matter

    Download chapter PDF

  2. Introduction

    Pages 1-2

  3. Global convergence of genetic algorithms: A markov chain analysis

    • A. E. Eiben, E. H. L. Aarts, K. M. Van Hee
    Pages 3-12

  4. The theory of virtual alphabets

    • David E. Goldberg
    Pages 13-22

  5. Towards an optimal mutation probability for genetic algorithms

    • Jürgen Hesser, Reinhard Männer
    Pages 23-32

  6. An alternative Genetic Algorithm

    • Jürgen Hesser, Reinhard Männer
    Pages 33-37

  7. An analysis of the interacting roles of population size and crossover in genetic algorithms

    • Kenneth A. De Jong, William M. Spears
    Pages 38-47

  8. Gleam a system for simulated "intuitive learning"

    • Christian Blume
    Pages 48-54

  9. Genetic algorithms and highly constrained problems: The time-table case

    • Alberto Colorni, Marco Dorigo, Vittorio Maniezzo
    Pages 55-59

  10. An evolution standing on the design of redundant manipulators

    • Yuval Davidor, Yaron Goldberg
    Pages 60-69

  11. Redundant coding of an NP-complete problem allows effective Genetic Algorithm search

    • Marleen Gerrits, Paulien Hogeweg
    Pages 70-74

  12. Circuit partitioning with genetic algorithms using a coding scheme to preserve the structure of a circuit

    • Martin Hulin
    Pages 75-79

  13. Genetic algorithms, production plan optimisation and scheduling

    • Philip Husbands, Frank Mill, Stephen Warrington
    Pages 80-84

  14. System identification using genetic algorithms

    • Timothy Johnson, Philip Husbands
    Pages 85-89

  15. Conformational analysis of DNA using genetic algorithms

    • C. B. Lucasius, S. Werten, A. H. J. M. van Aert, G. Kateman, M. J. J. Blommers
    Pages 90-97

  16. Operator-oriented genetic algorithm and its application to sliding block puzzle problem

    • Jung-Yul Suh, Chan-Do Lee
    Pages 98-103

  17. A topology exploiting genetic algorithm to control dynamic systems

    • Dirk Thierens, Leo Vercauteren
    Pages 104-108

  18. Genetic local search algorithms for the traveling salesman problem

    • Nico L. J. Ulder, Emile H. L. Aarts, Hans-Jürgen Bandelt, Peter J. M. van Laarhoven, Erwin Pesch
    Pages 109-116

  19. Genetic programming artificial nervous systems artificial embryos and embryological electronics

    • Hugo de Garis
    Pages 117-123

  20. Concept formation and decision tree induction using the genetic programming paradigm

    • John R. Koza
    Pages 124-128
Back to top

Other volumes

  1. Parallel Problem Solving from Nature

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation