Spiral inductor design based on fireworks optimization combined with free search. Jeronymo, D., Leite, J., Mariani, V., Dos Santos Coelho, L., & Goudos, S. In 2018 7th International Conference on Modern Circuits and Systems Technologies, MOCAST 2018, 2018.
abstract   bibtex   
© 2018 IEEE. Over the decades, metaheuristics, such as evolutionary and swarm intelligence paradigmms have been efficiently applied to solve real world engineering problems. Spiral inductors are widely used in radio frequency applications, such as voltage controlled oscillators, telemetry, matching networks and low noise amplifiers. However, the good performance of the spiral inductors represents a designing challenge. Metaheuristic method can be applied, in order to meet the design requirements of a spiral inductor. In this paper, an improved fireworks optimization algorithm (IFOA) combined with free search (FS) and opposition-based learning is proposed. The new algorithm is validated to optimize the number of turns for the spiral, the width of the turns, the separation between turns and the diameter for the inner-most turn of a spiral inductor which operates at 95 MHz. Simulation results indicate the promising performance of the improved FOA when compared with the classical FOA and a genetic algorithm in spiral inductors design application.
@inproceedings{
 title = {Spiral inductor design based on fireworks optimization combined with free search},
 type = {inproceedings},
 year = {2018},
 identifiers = {[object Object]},
 keywords = {fireworks optimization,optimization,radio frequency,spiral inductor,stochastic metaheuristics},
 id = {6adea789-431e-3a6b-9ee5-c4a3481cbfc9},
 created = {2020-02-29T16:57:44.044Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2020-02-29T16:57:44.044Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2018 IEEE. Over the decades, metaheuristics, such as evolutionary and swarm intelligence paradigmms have been efficiently applied to solve real world engineering problems. Spiral inductors are widely used in radio frequency applications, such as voltage controlled oscillators, telemetry, matching networks and low noise amplifiers. However, the good performance of the spiral inductors represents a designing challenge. Metaheuristic method can be applied, in order to meet the design requirements of a spiral inductor. In this paper, an improved fireworks optimization algorithm (IFOA) combined with free search (FS) and opposition-based learning is proposed. The new algorithm is validated to optimize the number of turns for the spiral, the width of the turns, the separation between turns and the diameter for the inner-most turn of a spiral inductor which operates at 95 MHz. Simulation results indicate the promising performance of the improved FOA when compared with the classical FOA and a genetic algorithm in spiral inductors design application.},
 bibtype = {inproceedings},
 author = {Jeronymo, D.C. and Leite, J.V. and Mariani, V.C. and Dos Santos Coelho, L. and Goudos, S.K.},
 booktitle = {2018 7th International Conference on Modern Circuits and Systems Technologies, MOCAST 2018}
}

Downloads: 0