RT Journal Article
T1 Evolutionary optimization algorithms for nonimaging optical design
A1 García Botella, Ángel
A1 Vázquez Moliní, Daniel
A1 García Fernández, Berta
A1 Álvarez Fernández-Balbuena, Antonio
AB Evolutionary optimization algorithms have been recently introduced as nonimaging optics design techniques. Unlike optimization of imaging systems, non sequential ray tracing simulations and complex non centred systems design must be considered, adding complexity to the problem. The Merit Function (MF) is a key element in the automatic optimization algorithm, nevertheless the selection of each objective's weight, {wi}, inside merit function needs a previous trial and error process for each optimization. The problem then is to determine appropriate weights value for each objective. In this paper we propose a new Dynamic Merit Function, DMF, with variable weight factors {wi(n)}. The proposed algorithm, automatically adapts weight factors, during the evolution of the optimization process. This dynamic merit function avoids the previous trial and error procedure selecting the right merit function and provides better results than conventional merit functions (CMF). Also we analyse the Multistart optimization algorithm applied in the flowline nonimaging design technique.
PB SPIE
SN 0277-786X
YR 2019
FD 2019-09-09
LK https://hdl.handle.net/20.500.14352/13618
UL https://hdl.handle.net/20.500.14352/13618
LA eng
NO Proceedings Volume 11120, Nonimaging Optics: Efficient Design for Illumination and Solar Concentration XVI; 111200M (2019)Event: SPIE Optical Engineering + Applications, 2019, San Diego, California, United StatesCopyright 2019. Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
DS Docta Complutense
RD 24 abr 2025