Application of dynamic merit function to nonimaging systems optimization
Automatic optimization algorithms have been recently introduced as nonimaging optics design techniques. Unlike optimization of imaging systems, nonsequential ray tracing simulations and complex noncentered systems design must be considered, adding complexity to the problem. The merit function is a k...
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| Published in | Optical engineering Vol. 54; no. 2; p. 025107 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Society of Photo-Optical Instrumentation Engineers
01.02.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0091-3286 1560-2303 |
| DOI | 10.1117/1.OE.54.2.025107 |
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| Abstract | Automatic optimization algorithms have been recently introduced as nonimaging optics design techniques. Unlike optimization of imaging systems, nonsequential ray tracing simulations and complex noncentered systems design must be considered, adding complexity to the problem. The merit function is a key element in the automatic optimization algorithm; nevertheless, the selection of each objective's weight, {wi}, inside the merit function needs a prior trial and error process for each optimization. The problem then is to determine appropriate weights' values for each objective. We propose a new dynamic merit function 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 by selecting the right merit function and provides better results than conventional merit functions. |
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| AbstractList | Automatic optimization algorithms have been recently introduced as nonimaging optics design techniques. Unlike optimization of imaging systems, nonsequential ray tracing simulations and complex noncentered systems design must be considered, adding complexity to the problem. The merit function is a key element in the automatic optimization algorithm; nevertheless, the selection of each objective's weight, {w sub()i, inside the merit function needs a prior trial and error process for each optimization. The problem then is to determine appropriate weights' values for each objective. We propose a new dynamic merit function with variable weight factors {w sub()in)}. 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 by selecting the right merit function and provides better results than conventional merit functions. Automatic optimization algorithms have been recently introduced as nonimaging optics design techniques. Unlike optimization of imaging systems, nonsequential ray tracing simulations and complex noncentered systems design must be considered, adding complexity to the problem. The merit function is a key element in the automatic optimization algorithm; nevertheless, the selection of each objective's weight, {wi}, inside the merit function needs a prior trial and error process for each optimization. The problem then is to determine appropriate weights' values for each objective. We propose a new dynamic merit function 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 by selecting the right merit function and provides better results than conventional merit functions. |
| Author | Fernández-Balbuena, Antonio Álvarez Montes, Mario González García-Botella, Angel Vázquez-Moliní, Daniel |
| Author_xml | – sequence: 1 givenname: Antonio Álvarez surname: Fernández-Balbuena fullname: Fernández-Balbuena, Antonio Álvarez email: antonioa@ucm.es organization: bUniversidad Complutense de Madrid, Departamento de Óptica, Fac de Óptica y Optometría. Arcos de Jalón, 118, 28037 Madrid, Spain – sequence: 2 givenname: Mario González surname: Montes fullname: Montes, Mario González organization: bUniversidad Complutense de Madrid, Departamento de Óptica, Fac de Óptica y Optometría. Arcos de Jalón, 118, 28037 Madrid, Spain – sequence: 3 givenname: Angel surname: García-Botella fullname: García-Botella, Angel organization: aUniversidad Politécnica de Madrid, Departamento de Física Aplicada a los Recursos Naturales, ETSI de Montes. Ciudad Universitaria s/n, 28040 Madrid, Spain – sequence: 4 givenname: Daniel surname: Vázquez-Moliní fullname: Vázquez-Moliní, Daniel organization: bUniversidad Complutense de Madrid, Departamento de Óptica, Fac de Óptica y Optometría. Arcos de Jalón, 118, 28037 Madrid, Spain |
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| Keywords | nonimaging systems dynamic weights dynamic merit function optical optimization |
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| SubjectTerms | Algorithms Automation Dynamical systems Dynamics Errors Evolution Optimization Systems design |
| Title | Application of dynamic merit function to nonimaging systems optimization |
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