Abstract
The paper deals with an application of the artificial immune system (AIS) and the particle swarm optimizer (PSO) to the optimization problems. The AIS and PSO are applied to optimize of stacking sequence of plies in composites. The optimization task is formulated as maximization of minimal difference between the first five eigenfrequencies and the external excitation frequency. Recently, immune and swarm methods have found various applications in mechanics, and also in structural optimization. The AIS is a computational adaptive system inspired by the principles, processes and mechanisms of biological immune systems. The algorithms typically use the characteristics of the immune systems like learning and memory to simulate and solve a problem in a computational manner. The swarm algorithms are based on the models of the animals social behaviours: moving and living in the groups. The main advantage of the AIS and PSO, contrary to gradient methods of optimization, is the fact that they do not need any information about the gradient of fitness function. The numerical examples demonstrate that the new method based on immune and particle computation is an effective technique for solving computer aided optimal design.
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
Balthrop, J., Esponda, F., Forrest, S., Glickman, M.: Coverage and generalization in an artificial immune system. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2002, pp. 3–10. Morgan Kaufmann, New York (2002)
Beluch, W., Burczyński, T., Kuś, W.: Evolutionary optimization and identification of hybrid laminates. Evolutionary Computation and Global Optimization 2006, Oficyna Wyd. Pol. Warszawskiej 156, 39–48 (2006)
Burczyński, T., Poteralski, A., Szczepanik, M.: Genetic generation of 2-D and 3-D structures. In: Second M.I.T. Conference on Computational Fluid and Solid Mechanics, Massa-Chusetts, Institute of Technology Cambridge, MA 02139 U.S.A (2003)
Burczyński, T., Poteralski, A., Szczepanik, M.: Topological evolutionary computing in the optimal design of 2D and 3D structures. Eng. Optimiz. Taylor and Francis 39(7), 811–830 (2007)
Burczyński, T., Bereta, M., Poteralski, A., Szczepanik, M.: Immune Computing: Intelligent Methodology and its applications in bioengineering and computational mechanics. In: Comput. Meth. Mech. Advanced Structured Materials, vol. 1, Springer, Heidelberg (2010)
Burczyński, T., Kuś, W., Długosz, A., Poteralski, A., Szczepanik, M.: Sequential and Distributed Evolutionary Computations in Structural Optimization. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol. 3070, pp. 1069–1074. Springer, Heidelberg (2004)
Burczyński, T., Długosz, A., Kus, W., Orantek, P., Poteralski, A., Szczepanik, M.: Intelligent computing in evolutionary optimal shaping of solids. In: Proceedings of the 3rd International Conference on Computing, Communications and Control Technologies, vol. 3, pp. 294–298 (2005)
de Castro, L.N., Timmis, J.: Artificial immune systems as a novel soft computing paradigm. Soft Computing 7(8), 526–544 (2003)
German, J.: Podstawy mechaniki kompozytów włóknistych, Wyd. Politechniki Krakowskiej, Kraków (2001)
Heppner, F., Grenander, U.: A stochastic nonlinear model for coordinated bird flocks. In: Krasner, S. (ed.) The Ubiquity of Chaos. AAAS Publications, Washington, DC (1990)
Kennedy, J., Eberhart, R.: Particle Swarm Optimisation. In: Proceedings of IEEE Int. Conf. on Neural Networks, Piscataway, NJ, pp. 1942–1948 (1995)
Kennedy, J., Eberhart, R.C.: Swarm Intelligence. Morgamn Kauffman (2001)
Mrozek, D., Małysiak-Mrozek, B.: An Improved Method for Protein Similarity Searching by Alignment of Fuzzy Energy Signatures. International Journal of Computational Intelligence Systems 4(1), 75–88 (2011)
Poteralski, A., Szczepanik, M., Dziatkiewicz, G., et al.: Immune identification of piezoelectric material constants using BEM. Inverse Problems in Science And Engineering 19(1), 103–116 (2011)
Poteralski, A., Szczepanik, M., Ptaszny, J., Ku, W., Burczyski, T.: Hybrid artificial immune system in identification of room acoustic properties Inverse Problems in Science and Engineering. Taylor and Francis (2013)
Poteralski, A., Szczepanik, M., Dziatkiewicz, G., Kuś, W., Burczyński, T.: Comparison between PSO and AIS on the basis of identification of material constants in piezoelectrics. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part II. LNCS (LNAI), vol. 7895, pp. 569–581. Springer, Heidelberg (2013)
Ptak, M., Ptak, W.: Basics of Immunology, Jagiellonian University Press, Cracow (2000) (in Polish)
Reynolds, C.W.: Flocks, herds, and schools, A distributed behavioral model. Computer Graphics 21, 25–34 (1987)
Silva, M.F.T., Borges, L.M.S.A., Rochinha, F.A., de Carvalho, L.A.V.: A genetic algo-rithm applied to composite elastic parameters identification. IPSE 12, 17–28 (2004)
Szczepanik, M., Poteralski, A., Długosz, A., Kuś, W., Burczyński, T.: Bio-inspired optimization of thermomechanical structures. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part II. LNCS (LNAI), vol. 7895, pp. 79–90. Springer, Heidelberg (2013)
Szczepanik, M., Poteralski, A., Ptaszny, J., Burczyński, T.: Hybrid Particle Swarm Optimizer and Its Application in Identification of Room Acoustic Properties. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) EC 2012 and SIDE 2012. LNCS, vol. 7269, pp. 386–394. Springer, Heidelberg (2012)
Tan, K.C., Goh, C.K., Mamun, A.A., Ei, E.Z.: An evolutionary artificial immune system for multi-objective optimization. European Journal of Operational Research, 371–392 (2008)
Tylikowski, A.: Teoria spreźystoci ciał anizotropowych jako elementw kompozytowych. VI Szkoła Kompozytów, Wisła, 183–200 (2003)
Wierzchoń, S.T.: Artificial Immune Systems, Theory and Applications. EXIT, Warsaw (2001)
Zilong, G., Sunan, W., Jian, Z.: A novel immune evolutionary algorithm incorporating chaos optimization. Pattern Recognition Letters 27, 2–8 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Poteralski, A., Szczepanik, M., Beluch, W., Burczyński, T. (2014). Optimization of Composite Structures Using Bio-inspired Methods. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8468. Springer, Cham. https://doi.org/10.1007/978-3-319-07176-3_34
Download citation
DOI: https://doi.org/10.1007/978-3-319-07176-3_34
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07175-6
Online ISBN: 978-3-319-07176-3
eBook Packages: Computer ScienceComputer Science (R0)