Multi-objective genetic algorithm applied to spectroscopic ellipsometry of organic-inorganic hybrid planar waveguides


The applicably of multi-objective optimization to ellipsometric data analysis is presented and a method to handle complex ellipsometric problems such as multi sample or multi angle analysis using multi-objective optimization is described. The performance of a multi-objective genetic algorithm (MOGA) is tested against a single objective common genetic algorithm (CGA). The procedure is applied to the characterization (refractive index and thickness) of planar waveguides intended for the production of optical components prepared sol-gel derived organic-inorganic hybrids, so-called di-ureasils, modified with zirconium tetrapropoxide, Zr(OPrn)(4) deposited on silica on silicon substrates. The results show that for the same initial conditions, MOGA performs better than the CGA, showing a higher success rate in the task of finding the best final solution. (C) 2010 Optical Society of America



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Fernandes, VR; Vicente, CMS; Wada, N; Andre, PS; Ferreira, RAS

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Funding was provided by Fundacao para a Ciencia e a Tecnologia, FEDER (PTDC/CTM/72093/2006, SFRH/BD/41943/2007) and COST Action MP0702. The authors also thank E. Pecoraro from Instituto de Telecomunicacoes, University of Aveiro, for help in the hybrids' synthesis.

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