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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 109
PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING
Edited by: Y. Tsompanakis, J. Kruis and B.H.V. Topping
Paper 35

Multi-Objective Reconstruction of Random Media using GPU Computing

A. Pospíšilová, J. Havelka and M. Lepš

Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague, Czech Republic

Full Bibliographic Reference for this paper
A. Pospí¬šilová, J. Havelka, M. Lep¬š, "Multi-Objective Reconstruction of Random Media using GPU Computing", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 35, 2015. doi:10.4203/ccp.109.35
Keywords: image reconstruction, multi-objective optimization, non-dominated sorting genetic algorithm II, two-point probability function, lineal path function, GPU.

Summary
This paper deals with a reconstruction of random media. The optimization with statistical descriptors (namely two-point probability function and two-point lineal path function) and minimizing the errors between the statistical descriptors evaluated on the original medium and on the reconstructed surrogate medium are utilized. AS a result of doubts concerning the setting of the weights in the weighted-sum method, a purely multi-objective optimization routine is selected, specifically the non-dominated sorting genetic algorithm II. The volume constraint is satisfied using a special mutation operator that interchanges only pixels from different phases which is the only operator used in the work described in this paper. As a result of the high computational demands, the lineal path was evaluated in a parallel fashion utilizing graphical processing units. The main contribution is in the testing of the proposed methodology on several benchmark images.

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