Skip to main content
SpringerLink
Log in
Book cover

AISB Workshop on Evolutionary Computing

AISB EC 1994: Evolutionary Computing pp 1–16Cite as

Formal memetic algorithms

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 865))

Abstract

A formal, representation-independent form of a memetic algorithm—a genetic algorithm incorporating local search—is introduced. A generalised form of N-point crossover is defined together with representation-independentpatching and hill-climbing operators. The resulting formal algorithm is then constructed and tested empirically on the travelling sales-rep problem. Whereas the genetic algorithms tested were unable to make good progress on the problems studied, the memetic algorithms performed very well.

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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • D. H. Ackley, 1987. A connectionist machine for genetic hillclimbing. Kluwer Academic Press, Boston.

    Google Scholar 

  • Thomas BÄck, Frank Hoffmeister, and Hans-Paul Schwefel, 1991. A survey of evolution strategies. In Proceedings of the Fourth International Conference on Genetic Algorithms. Morgan Kaufmann (San Mateo).

    Google Scholar 

  • Lawrence Davis, 1991. Handbook of Genetic Algorithms. Van Nostrand Reinhold (New York).

    Google Scholar 

  • Richard Dawkins, 1976. The Selfish Gene. Oxford University Press (Oxford).

    Google Scholar 

  • Martina Gorges-Schleuter, 1989. ASPARAGOS: an asynchronous parallel genetic optimization strategy. In Proceedings of the Third International Conference on Genetic Algorithms, pages 422–427. Morgan Kaufmann (San Mateo).

    Google Scholar 

  • John H. Holland, 1975. Adaptation in Natural and Artificial Systems. University of Michigan Press (Ann Arbor).

    Google Scholar 

  • E. L. Lawler, J. K. Lenstra, A. H. G. Rinnooy Kan, and D. B. Shmoys, 1985. The Travelling Salesman Problem: A Guided Tour of Combinatorial Optimisation. Wiley.

    Google Scholar 

  • Pablo Moscato and Michael G. Norman, 1992. A “memetic” approach for the travelling salesman problem — implementation of a computational ecology for combinatorial optimisation on message-passing systems. In Proceedings of the International Conference on Parallel Computing and Transputer Applications. IOS Press (Amsterdam).

    Google Scholar 

  • H. Mühlenbein, 1989. Parallel genetic algorithms, population genetics and combinatorial optimization. In Proceedings of the Third International Conference on Genetic Algorithms, pages 416–421. Morgan Kaufmann (San Mateo).

    Google Scholar 

  • Heinz Mühlenbein, 1992. How genetic algorithms really work. part I: Mutation and hillclimbing. In R. MÄnner and B. Manderick, editors, Parallel Problem Solving from Nature, 2. Elsevier Science Publishers/North Holland (Amsterdam).

    Google Scholar 

  • Nicholas J. Radcliffe, 1991. Equivalence class analysis of genetic algorithms. Complex Systems, 5(2):183–205.

    Google Scholar 

  • Nicholas J. Radcliffe, 1992. Genetic set recombination. In Darrell Whitley, editor, Foundations of Genetic Algorithms 2. Morgan Kaufmann (San Mateo, CA).

    Google Scholar 

  • Nicholas J. Radcliffe, 1994a. The algebra of genetic algorithms. To appear in Annals of Maths and Artificial Intelligence.

    Google Scholar 

  • Nicholas J. Radcliffe, 1994b. Fitness variance of formae and performance prediction. Technical report, To appear in Foundations of Genetic Algorithms 3.

    Google Scholar 

  • Gerhard Reinelt, 1990. TSPLIB.

    Google Scholar 

  • Patrick D. Surry and Nicholas J. Radcliffe, 1994. RPL2: A language and parallel framework for evolutionary computing. In Parallel Problem Solving from Nature III (to appear).

    Google Scholar 

  • M. G. A. Verhoeven, E. H. L. Aarts, E. van de Sluis, and R. J. M. Vaessens, 1992. Parallel local search and the travelling salesman problem. In R. MÄnner and B. Manderick, editors, Parallel Problem Solving From Nature, 2, pages 543–552. Elsevier Science Publishers/North Holland (Amsterdam).

    Google Scholar 

  • Darrell Whitley, Timothy Starkweather, and D'Ann Fuquay, 1989. Scheduling problems and traveling salesmen: The genetic edge recombination operator. In Proceedings of the Third International Conference on Genetic Algorithms. Morgan Kaufmann (San Mateo).

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Edinburgh Parallel Computing Centre King's Buildings, University of Edinburgh, EH9 3JZ, Scotland

    Nicholas J. Radcliffe & Patrick D. Surry

Authors
  1. Nicholas J. Radcliffe
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Patrick D. Surry
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Terence C. Fogarty

Rights and permissions

Reprints and permissions

Copyright information

© 1994 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Radcliffe, N.J., Surry, P.D. (1994). Formal memetic algorithms. In: Fogarty, T.C. (eds) Evolutionary Computing. AISB EC 1994. Lecture Notes in Computer Science, vol 865. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58483-8_1

Download citation

  • DOI: https://doi.org/10.1007/3-540-58483-8_1

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58483-4

  • Online ISBN: 978-3-540-48999-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation