Adaptive Non-Uniform Particle Swarm Application to Plasmonic Design

Author:

Kessentini Sameh1,Barchiesi Dominique1,Grosges Thomas1,Giraud-Moreau Laurence1,Lamy de la Chapelle Marc2

Affiliation:

1. University of Technology of Troyes, France

2. University of Paris XIII, France

Abstract

The metaheuristic approach has become an important tool for the optimization of design in engineering. In that way, its application to the development of the plasmonic based biosensor is apparent. Plasmonics represents a rapidly expanding interdisciplinary field with numerous transducers for physical, biological and medicine applications. Specific problems are related to this domain. The plasmonic structures design depends on a large number of parameters. Second, the way of their fabrication is complex and industrial aspects are in their infancy. In this study, the authors propose a non-uniform adapted Particle Swarm Optimization (PSO) for rapid resolution of plasmonic problem. The method is tested and compared to the standard PSO, the meta-PSO (Veenhuis, 2006) and the ANUHEM (Barchiesi, 2009).These approaches are applied to the specific problem of the optimization of Surface Plasmon Resonance (SPR) Biosensors design. Results show great efficiency of the introduced method.

Publisher

IGI Global

Subject

Decision Sciences (miscellaneous),Computational Mathematics,Computational Theory and Mathematics,Control and Optimization,Computer Science Applications,Modeling and Simulation,Statistics and Probability

Reference31 articles.

1. Barchiesi, D. (2009). Adaptive non-uniforme, hyperellitist evolutionary method for the optimization of plasmonic biosensors. In Proceedings of the International Conference on Computers & Industrial Engineering (pp. 542–547).

2. A Poincaré's approach for plasmonics: the plasmon localization

3. Barchiesi, D., Macias, D., Belmar-Letellier, L., Labeke, D. V., de la Chapelle, M. L., Toury, T., Kremer, E., et al. (2008b). Plasmonics: Influence of the intermediate

4. Carlisle, C., & Dozier, G. (2001). An off-the-shelf PSO. In Proceedings of the Particle Swarm Optimization Workshop (pp. 1-6).

5. Clerc, M. (2009). A method to improve standard PSO. Retrieved January 29, 2010, from http://clerc.maurice.free.fr/pso/Design_efficient_PSO.pdf

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