Abstract
This paper shows how evolutionary algorithms can be described in a concise, yet comprehensive and accurate way. A classification scheme is introduced and presented in a tabular form called TEA (Table of Evolutionary Algorithms). It distinguishes between different classes of evolutionary algorithms (e.g., genetic algorithms, ant systems) by enumerating the fundamental ingredients of each of these algorithms. At the end, possible uses of the TEA are illustrated on classical evolutionary algorithms.
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References
Bäck, Th. and H.-P. Schwefel. (1993). “An Overview of Evolutionary Algorithms for Parameter Optimization,” Evolutionary Computation 1, 1–23.
Colorni, A., M. Dorigo, and V. Maniezzo. (1991). “Distributed Optimization by Ant Colonies.” In MIT Press (ed.), First European Conference on Artificial Life, Bradford Books, pp. 134–142.
Colorni, A., M. Dorigo, and V. Maniezzo. (1992). “An Investigation of Some Properties of an Ant Algorithm.” In R. Männer and B. Manderick (eds.), Second European Conference on Parallel Problem Solving from Nature. Brussels: Elsevier Publishing, pp. 509–520.
Davis, L. (1991). Handbook of Genetic Algorithms. New York: Van Nostrand Reinhold.
Glover, F. (1977). “Heuristics for Integer Programming Using Surrogate Constraints,” Decision Sciences 8, 156–166.
Glover, F. (1994). “Genetic Algorithms and Scatter Search: Unsuspected Potentials,” Statistics and Computing 4, 131–140.
Glover and M. Laguna. (1997). Tabu Search. Norwell, MA: Kluwer Academic Publishers.
Goldberg, D. (1989). Genetics Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley: Publishing Company.
Heitkötter, J. and D. Beasley. (1997). The Hitch-Hiker's Guide to Evolutionary Computation (FAQ for comp.ai.genetic). URL:ftp://ftp.krl.caltech.edu/pub/EC/Welcome.html.
Holland, J. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
Kuntz, P. and D. Snyers. (1994). “Emergent Colonization and Graph Partitioning,” Third International Conference of Adaptative Behavior. MIT Press, pp. 494–500.
Rochat, Y. and E. Taillard. (1995). “Probabilistic Diversification and Intensification in Local Search for Vehicle Routing,” Journal of Heuristics 1, 147–167.
Spears, W.M. and K. DeJong. (1991). “An Analysis of Multi-Point Crossover.” In G.J.E. Rawlins (ed.), Foundations of Genetic Algorithms. Morgan Kaufmann, pp. 301–315.
Syswerda, G. (1989). “Uniform Crossover in Genetic Algorithms.” In J.D. Schaffer (ed.), Third International Conference on Genetic Algorithms. Morgan Kaufmann, pp. 2–9.
Zufferey, N. and A. Hertz. (1997). “Coloration de graphes `a l'aide de fourmis.” Technical Report, EPFL, Lausanne, Switzerland.
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Calégari, P., Coray, G., Hertz, A. et al. A Taxonomy of Evolutionary Algorithms in Combinatorial Optimization. Journal of Heuristics 5, 145–158 (1999). https://doi.org/10.1023/A:1009625526657
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DOI: https://doi.org/10.1023/A:1009625526657