Abstract
A simple evolutionary algorithm is theoretically compared with other methods of this class for a situation in which the operator of transition to new solutions satisfies the so-called monotonicity condition. This algorithm under the monotonicity condition is optimal in the class of evolutionary algorithms.
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REFERENCES
Goldberg, D.E., Genetic Algorithms in Search, Optimization, and Machine Learning, Reading: Addison Wesley, 1989.
Reeves, C.R., Genetic Algorithms for the Operations Researcher, INF J. Comput., 1997, vol. 9, no. 3, pp. 231–250.
Rechenberg, I., Evolutionsstrategie: optimerung technischer Systeme nach Prinzipen der Biologischen Evolution, Stuttgart: Formann-Holzboog Verlag, 1973.
Koza, J.R., Genetic Programming II: Automatic Discovery of Reusable Programs (Complex Adaptive Systems), Cambrige: MIT Press, 1994.
Darwin, C.R., On the Origin of Species, London: Cloves, 1860.
Beyer, H.-G., The Theory of Evolution Strategies. Natural Computing Series, Heidelberg: Springer, 2001.
Reeves, C.R. and Rowe, J.E., Genetic Algorithms: Principles and Perspectives, Norwell: Kluwer, 2002.
Vose, M.D., The Simple Genetic Algorithm: Foundations and Theory, Cambridge: MIT Press, 1999.
Rastrigin, L.A., Statisticheskie metody poiska (Statistical Search Methods), Moscow: Nauka, 1968.
Johnson, D.S., Aragon, C.R., McGeoch, L.A., and Schevon, C., Optimization by Simulated Annealing: An Experimental Evaluation. Part I. Graph Partitioning, Oper. Res., 1989, vol. 37, no. 6, pp. 865–892.
Borisovsky, P.A. and Eremeev, A.V., A Study on Performance of the (1+1)-Evolutionary Algorithm, in Foundations of Genetic Algorithms 7, De Jong, K., Poli R., and Rowe. J., Eds., San Francisco: Morgan Kaufmann, 2003.
Motwani, R. and Raghavan, P., Randomized Algorithms, Cambrige: Cambridge Univ. Press, 1995.
Rudolph, G., Finite Markov Chain Results in Evolutionary Computation: A Tour d'Horizon, Fundamenta Inf., 1998, vol. 35, no. 1-4, pp. 67–89.
Ermeev, A.V., Genetic Algorithms for Covering Problems, Diskret. Analiz Issl. Operatsii, 2000, vol. 7, no. 1, pp. 47–60.
Eremeev, A.V., Modeling and Analysis of Genetic Algorithms with Tournament Selection, in Proc. Artificial Evolution Conference (AE'99), Fonlupt, C., et al., Eds., Dunkerque: Springer Verlag, 2000, vol. 1829, pp. 84–95.
Aldous, D. and Vazirani, U.U., "Go with the Winners" Algorithms, Proc. IEEE Sympos, Foundations Comput. Sci., 1994, pp. 492–501.
Balas, E., A Sharp Bound on the Ratio Between Optimal Integer and Fractional Covers, Math. Oper. Res., 1984, vol. 9, no. 1, pp. 1–5.
Borisovsky, P.A. and Zavolovskaya, M.S., Experimental Comparison of Two Evolutionary Algorithms for the Independent Set Problem, in Application of Evolutionary Computers, Proc. EvoWorkshops 2000, Cagnoni, S., et al., Eds., Essex: Springer Verlag, 2003, vol. 2611, pp. 154–164.
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Borisovskii, P.A., Eremeev, A.V. Comparison of Certain Evolutionary Algorithms. Automation and Remote Control 65, 357–362 (2004). https://doi.org/10.1023/B:AURC.0000019365.10288.58
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DOI: https://doi.org/10.1023/B:AURC.0000019365.10288.58