Abstract
A co-operative method based on five biology-related optimization algorithms is used in solving crystal structures from X-ray diffraction data. This method does not need essential effort for its adjustment to the problem in hand but demonstrates high performance. This algorithm is compared with a sequential two-level genetic algorithm, a multi-population parallel genetic algorithm and a self-configuring genetic algorithm as well as with two problem specific approaches. It is demonstrated on a special crystal structure with 7 atoms and 21 degrees of freedom on which the co-operative swarm optimization algorithm exhibits comparative reliability but works faster than other used algorithms. Perspective directions for improving the approach are discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Inorganic Crystal Structure Database. FIZ Karlsruhe. http://www.fiz-karlsruhe.de/icsd.html
Cambridge Structural Database. Cambridge Crystallographic Data Centre. http://www.ccdc.cam.ac.uk/products/csd/
Dinnebier, R.E., Billinge, S.J.L.: Powder diffraction theory and practice. Royal Society of Chemistry, 507 (2008)
Young, R.A.: The rietveld method, p. 298. Oxford University Press (1995)
David, W.I.F., Shankland, K.: Structure determination from powder diffraction data. Acta Cryst. A64, 52–64 (2008)
Cerny, R., Favre-Nicolin, V.: Direct space methods of structure determination from powder diffraction: principles, guidelines, perspectives. Z. Kristallogr. 222, 105–113 (2007)
Kenneth, D., Harris M.: Fundamentals and applications of genetic algorithms for structure solution from powder X-ray diffraction data. Computational Materials Science 45(1) (2009)
Semenkin, E., Semenkina, M.: Self-configuring genetic algorithm with modified uniform crossover operator. In: Tan, Y., Shi, Y., Ji, Z. (eds.) ICSI 2012, Part I. LNCS, vol. 7331, pp. 414–421. Springer, Heidelberg (2012)
Akhmedova, Sh., Semenkin, E.: Co-operation of biology related algorithms. In: IEEE Congress on Evolutionary Computation (CEC 2013), pp. 2207–2214 (2013)
Yakimov, Y.I., Semenkin, E.S., Yakimov, I.S.: Two-level genetic algorithm for a fullprofile fitting of X-ray powder patterns. Z. Kristallogr. (30), 21–26 (2009)
Solovyov, L.A.: Full-profile refinement by derivative difference minimization. J. Appl. Cryst. 3, 743–749 (2004)
Yakimov, Y.I., Kirik, S.D., Semenkin, E.S., Solovyov, L.A., Yakimov, I.S.: The evolutionary method of modelling a crystal structure by powder diffraction data. Journal of Siberian Federal University (Chemistry) 6(2), 180–191 (2013)
Burakov, S.V., et al.: Multi-population two-level genetic algorithm for determination of crystal structure from X-ray powder diffraction data. In: Proceedings of Conference APMSIT-2014, Shanghai, China, pp. 13–14 (2014)
Semenkin, E., Semenkina, M.: Stochastic models and optimization algorithms for decision support in spacecraft control systems preliminary design. In: Ferrier, J.-L., Bernard, A., Gusikhin, O., Madani, K. (eds.) ICINCO 2012. LNEE, vol. 283, pp. 51–65. Springer, Heidelberg (2014)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: IEEE International Conference on Neural networks, IV, pp. 1942–1948 (1995)
Yang, Ch., Tu, X., Chen, J.: Algorithm of marriage in honey bees optimization based on the wolf pack search. In: International Conference on Intelligent Pervasive Computing, pp. 462–467 (2007)
Yang, X.-S.: Firefly algorithms for multimodal optimization. In: Watanabe, O., Zeugmann, T. (eds.) SAGA 2009. LNCS, vol. 5792, pp. 169–178. Springer, Heidelberg (2009)
Yang, X.S., Deb, S.: Cuckoo search via levy flights. In: World Congress on Nature & Biologically Inspired Computing, pp. 210–214. IEEE Publications (2009)
Yang, X.-S.: A new metaheuristic bat-inspired algorithm. In: González, J.R., Pelta, D.A., Cruz, C., Terrazas, G., Krasnogor, N. (eds.) NICSO 2010. SCI, vol. 284, pp. 65–74. Springer, Heidelberg (2010)
Akhmedova, S., Semenkin, E.: Data mining tools design with co-operation of biology related algorithms. In: Tan, Y., Shi, Y., Coello, C.A. (eds.) ICSI 2014, Part I. LNCS, vol. 8794, pp. 499–506. Springer, Heidelberg (2014)
Favre-Nicolin, V., Cerny, R.: FOX “free objects for crystallography”: a modular approach to ab initio structure determination from powder diffraction. J. Appl. Cryst. 35, 734–743 (2002)
Griffin, T.A.N., Shankland, K., Van de Streek, J., Cole, J.: GDASH: a grid-enabled program for structure solution from powder diffraction data. J. Appl. Cryst. 42, 356–359 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Zaloga, A. et al. (2015). On the Application of Co-Operative Swarm Optimization in the Solution of Crystal Structures from X-Ray Diffraction Data. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9140. Springer, Cham. https://doi.org/10.1007/978-3-319-20466-6_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-20466-6_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-20465-9
Online ISBN: 978-3-319-20466-6
eBook Packages: Computer ScienceComputer Science (R0)