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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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.
Arabas, J., Michalewicz, Z., and Mulawka, J., GAVaPS-a Genetic Algorithm with Varying Population Size, in [41].
BÄck, T., Fogel, D., and Michalewicz, Z. (Editors), Handbook of Evolutionary Computation, IOP Press, in preparation.
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.
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.
Belew, R. and Booker, L. (Editors), Proceedings of the Fourth International Conference on Genetic Algorithms, Morgan Kaufmann Publishers, Los Altos, CA, 1991.
De Jong, K.A., (Editor), Evolutionary Computation, MIT Press, 1993.
Brooke, A., Kendrick, D., and Meeraus, A., GAMS: A User's Guide, The Scientific Press, 1988.
Davis, L., (Editor), Genetic Algorithms and Simulated Annealing, Morgan Kaufmann Publishers, Los Altos, CA, 1987.
Davis, L., Adapting Operator Probabilities in Genetic Algorithms, in [44], pp. 61–69.
Davis, L. and Steenstrup, M., Genetic Algorithms and Simulated Annealing: An Overview, in [9], pp. 1–11.
De Jong, K., Genetic Algorithms: A 10 Year Perspective, in [27], pp. 169–177.
De Jong, K., Genetic Algorithms: A 25 Year Perspective, in [53], pp.125–134.
Dhar, V. and Ranganathan, N., Integer Programming vs. Expert Systems: An Experimental Comparison, Communications of ACM, Vol. 33, No.3, pp. 323–336, 1990.
Eshelman, L.J. and Schaffer, J.D., Preventing Premature Convergence in Genetic Algorithms by Preventing Incest, in [6], pp. 115–122.
Fogel, D.B., Evolving Artificial Intelligence, Ph.D. Thesis, University of California, San Diego, 1992.
Fogel, D.B. (Editor), IEEE Transactions on Neural Networks, special issue on Evolutionary Computation, Vol.5, No.1, 1994.
Fogel, D.B., An Introduction to Simulated Evolutionary Optimization, IEEE Transactions on Neural Networks, special issue on Evolutionary Computation, Vol.5, No.1, 1994.
Fogel, D.B. and Atmar, W., Proceedings of the First Annual Conference on Evolutionary Programming, La Jolla, CA, 1992, Evolutionary Programming Society.
Fogel, D.B. and Atmar, W., Proceedings of the Second Annual Conference on Evolutionary Programming, La Jolla, CA, 1993, Evolutionary Programming Society.
Fogel, L.J., Owens, A.J., and Walsh, M.J., Artificial Intelligence Through Simulated Evolution, John Wiley, Chichester, UK, 1966.
Fogel, L.J., Evolutionary Programming in Perspective: The Top-Down View, in [53], pp.135–146.
Forrest, S. (Editor), Proceedings of the Fifth International Conference on Genetic Algorithms, Morgan Kaufmann Publishers, Los Altos, CA, 1993.
Goldberg, D.E., Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, MA, 1989.
Goldberg, D.E., Deb, K., and Korb, B., Do not Worry, Be Messy, in [6], pp. 24–30.
Goldberg, D.E., Milman, K., and Tidd, C., Genetic Algorithms: A Bibliography, IlliGAL Technical Report 92008, 1992.
Grefenstette, J.J., (Editor), Proceedings of the First International Conference on Genetic Algorithms, Lawrence Erlbaum Associates, Hillsdale, NJ, 1985.
Grefenstette, J.J., (Editor), Proceedings of the Second International Conference on Genetic Algorithms, Lawrence Erlbaum Associates, Hillsdale, NJ, 1987.
Heitkötter, J., (Editor), The Hitch-Hiker's Guide to Evolutionary Computation, FAQ in comp.ai.genetic, issue 1.10, 20 December 1993.
Holland, J.H., Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, 1975.
Koza, J., Genetic Programming, MIT Press, 1992.
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.
Michalewicz, Z., A Hierarchy of Evolution Programs: An Experimental Study, Evolutionary Computation, Vol. 1, No.1, 1993, pp. 51–76.
Michalewicz, Z., Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, 2nd edition, 1994.
Michalewicz, Z. (Editor), Statistics & Computing, special issue on evolutionary computation, Vol.4, No.2, 1994.
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.
Mühlenbein, H. and Schlierkamp-Vosen, D., Predictive Models for the Breeder Genetic Algorithm, Evolutionary Computation, Vol. 1, No.1, pp. 25–49, 1993.
Nissen, V., Evolutionary Algorithms in Management Science: An Overview and List of References, European Study Group for Evolutionary Economics, 1993.
Orvosh, D. and Davis, L., Shall We Repair? Genetic Algorithms, Combinatorial Optimization, and Feasibility Constraints, in [23], p. 650.
Potter, M. and De Jong, K., A Cooperative Coevolutionary Approach to Function Optimization, George Mason University, 1994.
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.
Reeves, C.R., Modern Heuristic Techniques for Combinatorial Problems, Blackwell Scientific Publications, London, 1993.
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.
Schaffer, J., (Editor), Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufmann Publishers, Los Altos, CA, 1989.
Schaffer, J.D. and Morishima, A., An Adaptive Crossover Distribution Mechanism for Genetic Algorithms, in [28], pp. 36–40.
Schraudolph, N. and Belew, R., Dynamic Parameter Encoding for Genetic Algorithms, CSE Technical Report #CS90-175, University of San Diego, La Jolla, 1990.
Schwefel, H.-P., On the Evolution of Evolutionary Computation, in [53], pp.116–124.
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.
Sebald, A.V. and Fogel, L. J., Proceedings of the Third Annual Conference on Evolutionary Programming, San Diego, CA, 1994, World Scientific.
Shaefer, C.G., The ARGOT Strategy: Adaptive Representation Genetic Optimizer Technique, in [28], pp. 50–55.
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.
Whitley, D., Genetic Algorithms: A Tutorial, in [35], pp.65–85.
Zurada, J., Marks, R., and Robinson, C. (Editors), Computational Intelligence-Imitating Life, IEEE Press, 1994.
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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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