Improving the lighting performance of a 3535 packaged hi-power LED using genetic programming, quality loss functions and particle swarm optimization

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@Article{Hsu20122933,
  author =       "Chih-Ming Hsu",
  title =        "Improving the lighting performance of a 3535 packaged
                 hi-power LED using genetic programming, quality loss
                 functions and particle swarm optimization",
  journal =      "Applied Soft Computing",
  volume =       "12",
  number =       "9",
  pages =        "2933--2947",
  year =         "2012",
  ISSN =         "1568-4946",
  DOI =          "doi:10.1016/j.asoc.2012.04.023",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1568494612002165",
  keywords =     "genetic algorithms, genetic programming,
                 Light-emitting diode, Lighting performance, Taguchi
                 quality loss functions, Particle swarm optimization,
                 Multi-response parameter design",
  abstract =     "The lighting performance of a 3535 packaged hi-power
                 LED (light-emitting diode) is mainly influenced by its
                 geometric design and the refractive properties of its
                 materials. In the past, engineers often determined the
                 settings of the geometric parameters and selected the
                 refractive properties of the materials through a
                 trial-and-error process based on the principles of
                 optics and their own experience. This procedure was
                 costly and time-consuming, and its use did not ensure
                 that the settings of the design parameters were
                 optimal. Therefore, this study proposed a hybrid
                 approach based on genetic programming (GP), Taguchi
                 quality loss functions, and particle swarm optimisation
                 (PSO) to solve the multi-response parameter design
                 problems. The feasibility and effectiveness of the
                 proposed approach was demonstrated by a case study on
                 improving the lighting performance of an LED. The
                 confirmation results showed that all of the key quality
                 characteristics of an LED fulfil the required
                 specifications, and the comparison found that the
                 proposed hybrid approach outperforms the traditional
                 Taguchi method in solving this multi-response parameter
                 design problem. The proposed hybrid approach can be
                 extended to solve parameter design problems with
                 multiple responses in various application fields.",
}

Genetic Programming entries for Chih-Ming Hsu

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