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Evolutionary Computing

AISB Workshop, Sheffield, U.K., April 3 - 4, 1995. Selected Papers

  • Conference proceedings
  • © 1995

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Editors:
  1. Terence C. Fogarty
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 993)

Included in the following conference series:

Conference proceedings info: AISB EC 1995.

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About this book

This volume is based on the Workshop on Evolutionary Computing held in Sheffield, U.K., in April 1995 under the sponsorship of the Society for the Study of Artificial Intelligence and Simulation of Behavior (AISB).
The 18 full papers presented were selected during a post-workshop refereeing meeting and chosen from 32 submissions for the workshop.
The papers are organized in sections on evolutionary computing theory and techniques, timetabling, routing and scheduling, optimization, signal processing and control, and genetic programming. The collection of papers has a certain bias towards real world applications of evolutionary computing and particularly genetic algorithms.

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Table of contents (19 papers)

  1. Front Matter

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  2. Some combinatorial landscapes on which a Genetic Algorithm outperforms other Stochastic iterative methods

    • Dave Corne, Peter Ross
    Pages 1-13

  3. Maximum entropy analysis of genetic algorithm operators

    • Jonathan L. Shapiro, Adam Prügel-Bennett
    Pages 14-24

  4. The ant colony metaphor for searching continuous design spaces

    • G. Bilchev, I. C. Parmee
    Pages 25-39

  5. Broadcast based fitness sharing GA for conflict resolution among autonomous robots

    • Sadayoshi Mikami, Yukinori Kakazu, Terence C. Fogarty
    Pages 40-47

  6. An adaptive poly-parental recombination strategy

    • Jim Smith, T. C. Fogarty
    Pages 48-61

  7. Neighbourhood seeding to reduce problem modality

    • A. J. Swann
    Pages 62-74

  8. Specialised recombinative operators for timetabling problems

    • Edmund Burke, David Elliman, Rupert Weare
    Pages 75-85

  9. The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms

    • Ben Paechter, Andrew Cumming, Henri Luchian
    Pages 86-93

  10. Comparing genetic algorithms, simulated annealing, and stochastic hillclimbing on timetabling problems

    • Peter Ross, Dave Corne
    Pages 94-102

  11. Evolutionary learning in computational ecologies: An application to adaptive distributed routing in communication networks

    • Brian Carse, Terence C. Fogarty, Alistair Munro
    Pages 103-116

  12. The radio link frequency assignment problem: A case study using genetic algorithms

    • A. Kapsalis, P. Chardaire, V. J. Rayward-Smith, G. D. Smith
    Pages 117-131

  13. Scheduling planned maintenance of the national grid

    • W. B. Langdon
    Pages 132-153

  14. Genetic operators and constraint handling for pipe network optimization

    • Dragan A. Savic, Godfrey A. Walters
    Pages 154-165

  15. A multi-objective approach to constrained optimisation of gas supply networks: The COMOGA method

    • Patrick D. Surry, Nicholas J. Radcliffe, Ian D. Boyd
    Pages 166-180

  16. Ternary decision diagram optimisation of Reed-Muller logic functions using a genetic algorithm for variable and simplification rule ordering

    • J. F. Miller, P. Thomson, P. V. G. Bradbeer
    Pages 181-190

  17. An evolutionary algorithm for parametric array signal processing

    • Dekun Yang, Stuart Flockton
    Pages 191-199

  18. Constraints on task and search complexity in GA+NN models of learning and adaptive behaviour

    • Mukesh J. Patel
    Pages 200-223

  19. Load balancing application of the genetic algorithm in a nonstationary environment

    • Frank Vavak, Terence C. Fogarty, Phillip Cheng
    Pages 224-233

  20. Exploring some commercial applications of genetic programming

    • Gerald Robinson, Paul McIlroy
    Pages 234-264
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