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              <p>In this paper the Evolutionary Method (EM) and the Particle Swarm Optimization (PSO), which are based on competitiveness and collaborative algorithms respectively, are investigated for plasmonic design. Actually, plasmonics represents a rapidly expanding interdisciplinary field with numerous devices for physical, biological and medicine applications. In this study, four EM and PSO algorithms are tested in two different plasmonic applications: design of surface plasmon resonance (SPR) based biosensors and optimization of hollow nanospheres used in curative purposes (cancer photothermal therapy). Specific problems-in addition of being multimodal and having different topologies are related to plasmonic design; therefore the most efficient optimization method should be determined through a comparative study. Results of simulations enable also to characterize the optimization methods and depict in which case they are more efficient.</p>
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