Abstract
A recently introduced method for the learning of the asymptotic marginal densities of stochastic search processes in optimization is generalized for its application in problems under constraints and uncertainty. The use of the proposed approach as a mechanism for diversification in optimization algorithms is illustrated on several benchmark examples.
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References
Michalewicz, Z.: A survey of constraint handling techniques in evolutionary computation methods. In: Proc. of the 4th Annual Conf. on Evolutionary Programming, pp. 135–155. MIT Press, Cambridge (1995)
Berrones, A.: Generating Random Deviates Consistent with the Long Term Behavior of Stochastic Search Processes in Global Optimization. In: Sandoval, F., Gonzalez Prieto, A., Cabestany, J., Graña, M. (eds.) IWANN 2007. LNCS, vol. 4507, pp. 1–8. Springer, Heidelberg (2007)
Berrones, A.: Stationary probability density of stochastic search processes in global optimization. J. Stat. Mech., P01013 (2008)
Peña, D., Sánchez, R., Berrones, A.: Stationary Fokker–Planck Learning for the Optimization of Parameters in Nonlinear Models. In: Gelbukh, A., Kuri Morales, Á.F. (eds.) MICAI 2007. LNCS (LNAI), vol. 4827, pp. 94–104. Springer, Heidelberg (2007)
Risken, H.: The Fokker–Planck Equation. Springer, Berlin (1984)
Van Kampen, N.G.: Stochastic Processes in Physics and Chemistry. North-Holland, Amsterdam (1992)
Osyczka, A., Krenich, S.: Evolutionary Algorithms for Global Optimization. In: Pintér, J. (ed.) Global Optimization, Scientific and Engineering Case Studies Series: Nonconvex Optimization and Its Applications, vol. 85 (2006)
Pulido, G.T., Coello, C.A.C.: A constraint-handling mechanism for particle swarm optimization. In: Proceedings of the 2004 congress on evolutionary computation, vol. 2, pp. 1396–1403 (2004)
Birge, J.R., Louveaux, F.: Introduction to Stochastic Programming. Springer, Berlin (1997)
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Velasco, J., Muñiz, A.L., Berrones, A. (2008). Learning Probability Densities of Optimization Problems with Constraints and Uncertainty. In: Gelbukh, A., Morales, E.F. (eds) MICAI 2008: Advances in Artificial Intelligence. MICAI 2008. Lecture Notes in Computer Science(), vol 5317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88636-5_25
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DOI: https://doi.org/10.1007/978-3-540-88636-5_25
Publisher Name: Springer, Berlin, Heidelberg
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