Asymptotic guarantee of success of the hp-HGS strategy

• Autorzy: Schaefer R. , Bambosz B. , Paszyński M.
• Konferencja: Evolutionary Computation and Global Optimization 2008 / National Conference (11 ; 2-4.06.2008 ; Szymbark, Poland)
• Języki publikacji: EN

Abstrakty

EN

We presented the new hp-UGS (hp adaptive FEM, Hierarchical Genetic Strategy) multi-deme, genetic strategy which cau be used for solving parametric inverse problems formulated as the global optimization ones. Its efficiency follows from the coupled adaptation of accuracy derived from the proper balance between the accuracy of hp-FEM used for solving direct problem and the accuracy of solving optimization problem. It is shown, that hp-HGS can find at least the same set of local extremes as the Simple Genetic Algorithm (SGA). Moreover, the results of asymptotic analysis that verify much less computational cost of hp-HGS are recalled from the previous papers.

Słowa kluczowe

EN

evolutionary algorithm; EA; genetic algorithm; evolutionary computation; simple genetic algorithm; SGA; Hierarchical Genetic Strategy; HGS; global optimization

PL

algorytm ewolucyjny; algorytm genetyczny; obliczenia ewolucyjne; optymalizacja globalna

• Wydawca: Oficyna Wydawnicza Politechniki Warszawskiej
• Czasopismo: Prace Naukowe Politechniki Warszawskiej. Elektronika
• Rocznik: 2008
• Tom: z. 165
• Strony: 189--196
• Opis fizyczny: Bibliogr. 12 poz.

Twórcy

autor

Schaefer R.

autor

Bambosz B.

autor

Paszyński M.

• Department of Computer Science, University of Science and Technology, Cracow, Poland,

Bibliografia

• [1] Ciarlet P.; The Finite Element Method for Elliptic. Problems. Society for Industrial & Applied, 2002.
• [2] Demkowicz L.: Computing with hp-Adaptive Finite Elements. Volume I. One- and Two- Dimensional Elliptic and Maxwell Problems, Chapmann & Hall / CRC Applied Matheniatics and Nonlinear Science, 2006.
• [3] Guus C., Boender E., Romeijn E.H.; Stochastic Methods. in Horst R., Pardalos P., M.; Handbook of Global Optimization, Kluwer 1995.
• [4] Kołodziej J.; Hierarchical Strategies of the Genetic Global Optimization. PhD Thesis. Jagiellonian University, Faculty of Mathematics and Informatics, Kraków 2003, Poland (in Polish).
• [5] Schaefer R., Barabasz B., Paszyński M.; Twin adaptive scheme for solving inverse problems. Proc. of Conf. on Evolutionary Algorithms and Global Optimization KAEiOG 2007, 2007, pp. 241-249.
• [6] Schaefer R. (with the chapter 6 written by Telega H.); Foundation of Genetic Global Optimization, Studies in Computational Intelligence Series 74, Springer 2007.
• [7] Schaefer R., Kołodziej J.; Genetic search reinforced by the population hierarchy, in De Jong K.A., Poli R., Rowe J.E. eds. Foundations of Genetic Algorithms 7, Morgan Kaufman Publisher 2003, pp. 383-399.
• [8] Schaefer R., Jabłoński Z.J.; How to Gain More Information from the Evolving Population? Chapter in: Arabas J. ed. Evolutionary Computation and Global Optimization. Warsaw Technical University Press 2002, pp. 21-33.
• [9] Schaefer R., Barabasz B.; Asymptotic behavior of hp-HGS (hp-adaptive Finite Element Method coupled with the Hierarchic Genetic Strategy) by solving inverse problems. Accepted to ICCS 2008.
• [10] Paszyński M., Barabasz B., Schaefer R.; Efficient adaptive strategy for solving inverse problems. LNCS Vol. 4487, Springer 2007, pp. 342-349.
• [11] Paszyński M., Szeliga D., Barabasz B., Macioł P.; An algorithm for relating convergence ratios of inverse and direct problem solutions by means of the self-adaptive lip finite element method. 17-th International Conference on Computer Methods in Mechanics, June 19-22, 2007, Spała, Poland.
• [12] Vose M.. D.; The Simple Genetic Algorithm. MIT Press, 1999.