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A perspective on evolutionary computation

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Progress in Evolutionary Computation (EvoWorkshops 1993, EvoWorkshops 1994)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 956))

Abstract

During the last three decades there has been a growing interest in algorithms which rely on analogies to natural processes. The emergence of massively parallel computers made these algorithms of practical interest. The best known algorithms in this class include evolutionary programming, genetic algorithms, evolution strategies, simulated annealing, classifier systems, and neural networks.

In this paper we discuss a subclass of these algorithms—those which are based on the principle of evolution (survival of the fittest). A common term, recently accepted, refers to such techniques as ‘evolutionary computation’ methods.

The paper presents a perspective of the field of evolutionary computation. It discusses briefly the concept of evolutionary computation, presents the author's first experience with these methods, provides a discussion on relationship between evolutionary computation techniques and the problem specific knowledge, and identifies some current critical issues.

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References

  1. Alander, J.T., An Indexed Bibliography of Genetic Algorithms: Years 1957–1993, Department of Information Technology and Production Economics, University of Vaasa, Finland, Report Series No.94–1, 1994.

    Google Scholar 

  2. Arabas, J., Michalewicz, Z., and Mulawka, J., GAVaPS-a Genetic Algorithm with Varying Population Size, in [41].

    Google Scholar 

  3. BÄck, T., Fogel, D., and Michalewicz, Z. (Editors), Handbook of Evolutionary Computation, IOP Press, in preparation.

    Google Scholar 

  4. Beasley, D., Bull, D.R., and Martin, R.R., An Overview of Genetic Algorithms: Part 1, Foundations, University Computing, Vol.15, No.2, pp.58–69, 1993.

    Google Scholar 

  5. Beasley, D., Bull, D.R., and Martin, R.R., An Overview of Genetic Algorithms: Part 2, Research Topics, University Computing, Vol.15, No.4, pp.170–181, 1993.

    Google Scholar 

  6. Belew, R. and Booker, L. (Editors), Proceedings of the Fourth International Conference on Genetic Algorithms, Morgan Kaufmann Publishers, Los Altos, CA, 1991.

    Google Scholar 

  7. De Jong, K.A., (Editor), Evolutionary Computation, MIT Press, 1993.

    Google Scholar 

  8. Brooke, A., Kendrick, D., and Meeraus, A., GAMS: A User's Guide, The Scientific Press, 1988.

    Google Scholar 

  9. Davis, L., (Editor), Genetic Algorithms and Simulated Annealing, Morgan Kaufmann Publishers, Los Altos, CA, 1987.

    Google Scholar 

  10. Davis, L., Adapting Operator Probabilities in Genetic Algorithms, in [44], pp. 61–69.

    Google Scholar 

  11. Davis, L. and Steenstrup, M., Genetic Algorithms and Simulated Annealing: An Overview, in [9], pp. 1–11.

    Google Scholar 

  12. De Jong, K., Genetic Algorithms: A 10 Year Perspective, in [27], pp. 169–177.

    Google Scholar 

  13. De Jong, K., Genetic Algorithms: A 25 Year Perspective, in [53], pp.125–134.

    Google Scholar 

  14. Dhar, V. and Ranganathan, N., Integer Programming vs. Expert Systems: An Experimental Comparison, Communications of ACM, Vol. 33, No.3, pp. 323–336, 1990.

    Google Scholar 

  15. Eshelman, L.J. and Schaffer, J.D., Preventing Premature Convergence in Genetic Algorithms by Preventing Incest, in [6], pp. 115–122.

    Google Scholar 

  16. Fogel, D.B., Evolving Artificial Intelligence, Ph.D. Thesis, University of California, San Diego, 1992.

    Google Scholar 

  17. Fogel, D.B. (Editor), IEEE Transactions on Neural Networks, special issue on Evolutionary Computation, Vol.5, No.1, 1994.

    Google Scholar 

  18. Fogel, D.B., An Introduction to Simulated Evolutionary Optimization, IEEE Transactions on Neural Networks, special issue on Evolutionary Computation, Vol.5, No.1, 1994.

    Google Scholar 

  19. Fogel, D.B. and Atmar, W., Proceedings of the First Annual Conference on Evolutionary Programming, La Jolla, CA, 1992, Evolutionary Programming Society.

    Google Scholar 

  20. Fogel, D.B. and Atmar, W., Proceedings of the Second Annual Conference on Evolutionary Programming, La Jolla, CA, 1993, Evolutionary Programming Society.

    Google Scholar 

  21. Fogel, L.J., Owens, A.J., and Walsh, M.J., Artificial Intelligence Through Simulated Evolution, John Wiley, Chichester, UK, 1966.

    Google Scholar 

  22. Fogel, L.J., Evolutionary Programming in Perspective: The Top-Down View, in [53], pp.135–146.

    Google Scholar 

  23. Forrest, S. (Editor), Proceedings of the Fifth International Conference on Genetic Algorithms, Morgan Kaufmann Publishers, Los Altos, CA, 1993.

    Google Scholar 

  24. Goldberg, D.E., Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, MA, 1989.

    Google Scholar 

  25. Goldberg, D.E., Deb, K., and Korb, B., Do not Worry, Be Messy, in [6], pp. 24–30.

    Google Scholar 

  26. Goldberg, D.E., Milman, K., and Tidd, C., Genetic Algorithms: A Bibliography, IlliGAL Technical Report 92008, 1992.

    Google Scholar 

  27. Grefenstette, J.J., (Editor), Proceedings of the First International Conference on Genetic Algorithms, Lawrence Erlbaum Associates, Hillsdale, NJ, 1985.

    Google Scholar 

  28. Grefenstette, J.J., (Editor), Proceedings of the Second International Conference on Genetic Algorithms, Lawrence Erlbaum Associates, Hillsdale, NJ, 1987.

    Google Scholar 

  29. Heitkötter, J., (Editor), The Hitch-Hiker's Guide to Evolutionary Computation, FAQ in comp.ai.genetic, issue 1.10, 20 December 1993.

    Google Scholar 

  30. Holland, J.H., Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, 1975.

    Google Scholar 

  31. Koza, J., Genetic Programming, MIT Press, 1992.

    Google Scholar 

  32. MÄnner, R. and Manderick, B. (Editors), Proceedings of the Second International Conference on Parallel Problem Solving from Nature (PPSN), North-Holland, Elsevier Science Publishers, Amsterdam, 1992.

    Google Scholar 

  33. Michalewicz, Z., A Hierarchy of Evolution Programs: An Experimental Study, Evolutionary Computation, Vol. 1, No.1, 1993, pp. 51–76.

    Google Scholar 

  34. Michalewicz, Z., Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, 2nd edition, 1994.

    Google Scholar 

  35. Michalewicz, Z. (Editor), Statistics & Computing, special issue on evolutionary computation, Vol.4, No.2, 1994.

    Google Scholar 

  36. Michalewicz, Z., Vignaux, G.A., and Hobbs, M., A Non-Standard Genetic Algorithm for the Nonlinear Transportation Problem, ORSA Journal on Computing, Vol. 3, No.4, 1991, pp. 307–316.

    Google Scholar 

  37. Mühlenbein, H. and Schlierkamp-Vosen, D., Predictive Models for the Breeder Genetic Algorithm, Evolutionary Computation, Vol. 1, No.1, pp. 25–49, 1993.

    Google Scholar 

  38. Nissen, V., Evolutionary Algorithms in Management Science: An Overview and List of References, European Study Group for Evolutionary Economics, 1993.

    Google Scholar 

  39. Orvosh, D. and Davis, L., Shall We Repair? Genetic Algorithms, Combinatorial Optimization, and Feasibility Constraints, in [23], p. 650.

    Google Scholar 

  40. Potter, M. and De Jong, K., A Cooperative Coevolutionary Approach to Function Optimization, George Mason University, 1994.

    Google Scholar 

  41. Proceedings of the First IEEE International Conference on Evolutionary Computation, Z. Michalewicz, J.D. Schaffer, H.-P. Schwefel, H. Kitano, D. Fogel (Editors), Orlando, 26 June–2 July, 1994.

    Google Scholar 

  42. Reeves, C.R., Modern Heuristic Techniques for Combinatorial Problems, Blackwell Scientific Publications, London, 1993.

    Google Scholar 

  43. Saravanan, N. and Fogel, D.B., A Bibliography of Evolutionary Computation & Applications, Department of Mechanical Engineering, Florida Atlantic University, Technical Report No. FAU-ME-93-100, 1993.

    Google Scholar 

  44. Schaffer, J., (Editor), Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufmann Publishers, Los Altos, CA, 1989.

    Google Scholar 

  45. Schaffer, J.D. and Morishima, A., An Adaptive Crossover Distribution Mechanism for Genetic Algorithms, in [28], pp. 36–40.

    Google Scholar 

  46. Schraudolph, N. and Belew, R., Dynamic Parameter Encoding for Genetic Algorithms, CSE Technical Report #CS90-175, University of San Diego, La Jolla, 1990.

    Google Scholar 

  47. Schwefel, H.-P., On the Evolution of Evolutionary Computation, in [53], pp.116–124.

    Google Scholar 

  48. Schwefel, H.-P. and MÄnner, R. (Editors), Proceedings of the First International Conference on Parallel Problem Solving from Nature (PPSN), Springer-Verlag, Lecture Notes in Computer Science, Vol.496, 1991.

    Google Scholar 

  49. Sebald, A.V. and Fogel, L. J., Proceedings of the Third Annual Conference on Evolutionary Programming, San Diego, CA, 1994, World Scientific.

    Google Scholar 

  50. Shaefer, C.G., The ARGOT Strategy: Adaptive Representation Genetic Optimizer Technique, in [28], pp. 50–55.

    Google Scholar 

  51. Vignaux, G.A., and Michalewicz, Z., A Genetic Algorithm for the Linear Transportation Problem, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 21, No.2, 1991, pp. 445–452.

    Google Scholar 

  52. Whitley, D., Genetic Algorithms: A Tutorial, in [35], pp.65–85.

    Google Scholar 

  53. Zurada, J., Marks, R., and Robinson, C. (Editors), Computational Intelligence-Imitating Life, IEEE Press, 1994.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of North Carolina, 28223, Charlotte, NC, USA

    Zbigniew Michalewicz

Authors
  1. Zbigniew Michalewicz
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Editor information

Xin Yao

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© 1995 Springer-Verlag Berlin Heidelberg

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Michalewicz, Z. (1995). A perspective on evolutionary computation. In: Yao, X. (eds) Progress in Evolutionary Computation. EvoWorkshops EvoWorkshops 1993 1994. Lecture Notes in Computer Science, vol 956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60154-6_49

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  • DOI: https://doi.org/10.1007/3-540-60154-6_49

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60154-8

  • Online ISBN: 978-3-540-49528-4

  • eBook Packages: Springer Book Archive

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