Abstract
This paper presents two nature-inspired approaches to the design of Zero Reference Codes (ZRC) for optical applications, both in one and two dimensions. Specifically we present a genetic algorithm and a simulated annealing hybridized with a restricted search operator to cope with the problem constraints. Extensive experiments have shown that nature-inspired approaches proposed can improve the results of existing techniques for this problem.
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References
Goldberg, D.E.: Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Reading (1989)
Yang, X., Yin, C.: A new method for the design of zero reference marks for grating measurement systems. J. Phys. E Sci. Instrum. 19, 34–37 (1986)
Yajun, L.: Autocorrelation function of a bar code system. J. Mod. Opt. 34, 1571–1575 (1987)
Yajun, L.: Optical valve using bar codes. Optik 79, 67–74 (1988)
Sáez-Landete, J., Alonso, J., Bernabeu, E.: Design of zero reference codes by means of a global optimization method. Optics Express 13, 195–201 (2004)
Chen, Y., Huang, W., Dang, X.: Design and analysis of two-dimensional zero-reference marks for alignment systems. Review of Scientific Instruments 74, 3549–3553 (2003)
Séz-Landete, J., Alonso, J., Bernabeu, E.: Design of two-dimensional zero reference codes by means of a global optimization method. Optics Express 13, 4230–4236 (2005)
Jones, D.R.: DIRECT Global optimization algorithm. In: Encyclopedia of Optimization, Kluwer Academic Publishers, Dordrecht (2001)
Salcedo-Sanz, S.S., Camps-Vals, G., Pŕez-Cruz, F., Sepúlveda-Sanchís, J., Bousoño-Calzón, C.: Enhancing genetic feature selection through restricted search and walsh analysis. IEEE Trans. System, Man and Cybern. Part C 34(4), 398–406 (2005)
Kirpatrick, S., Gerlatt, C.D., Vecchi, M.P.: Optimization by simulated annealing. Science 220, 671–680 (1983)
Kirpatrick, S.: Optimization by simulated annealing–Quantitative studies. J. Stat. Phys. 34, 975–986 (1984)
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© 2006 Springer-Verlag Berlin Heidelberg
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Salcedo-Sanz, S., Saez-Landete, J., Rosa-Zurera, M. (2006). Nature-Inspired Algorithms for the Optimization of Optical Reference Signals. In: Runarsson, T.P., Beyer, HG., Burke, E., Merelo-Guervós, J.J., Whitley, L.D., Yao, X. (eds) Parallel Problem Solving from Nature - PPSN IX. PPSN 2006. Lecture Notes in Computer Science, vol 4193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11844297_29
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DOI: https://doi.org/10.1007/11844297_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38990-3
Online ISBN: 978-3-540-38991-0
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