Optical design with the aid of a genetic algorithm

BioSystems

Volumn 37, Issue 3, 1996, Pages 177-187

  Van Leijenhorst, Derek C ^a   Lucasius, Carlos B ^b   Thijssen, Jos M ^a  

^a RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

^b DALHOUSIE UNIVERSITY   (Canada)

Author keywords

Genetic algorithms; Geometrical optics; Optical design; Optimization; Ray tracing

Indexed keywords

ALGORITHM; ARTICLE; FEASIBILITY STUDY; GENETICS; OPTICS; VISUAL SYSTEM;

EID: 0030046226     PISSN: 03032647     EISSN: None     Source Type: Journal    
DOI: 10.1016/0303-2647(95)01556-6     Document Type: Article

References (17)

1. Caruana, R.A. and Schaffer, J.D., 1988, Representation and hidden bias: Gray vs. binary coding for genetic algorithms, in: Proceedings of the Fifth International Conference on Machine Learning, J.E. Laird (ed.) (Los Altos, CA, Morgan Kaufmann) pp. 153-161.
2. Davis, L., editor, 1991, Handbook of Genetic Algorithms (Van Nostrand Reinhold).
3. Eshelman, L.J., Caruana, R.A. and Schaffer, J.D., Biases in the Crossover Landscape, Proceedings of the Third International Conference on Genetic Algorithms (San Mateo, CA, 1989, Morgan Kaufmann) pp. 10-19.
4. Frieden, B.R., editor, 1980, The Computer in Optical Research, Topics in Applied Physics Volume 41 (Springer, New York, NY).
5. Goldberg, D.E., 1989, Genetic Algorithms in Search, Optimization and Machine Learning (Addison-Wesley, Reading, MA).
6. van Heel, A.C.S., 1958, Inleiding in de Optica (English: Introduction to Optics), 4th edition (Martinus Nijhoff).
7. Holland, J.H., 1992, Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, MI, 1975; Revised print: MIT Press, Cambridge, MA.
8. van Leijenhorst, D.C., Lucasius, C.B. and Thijssen, J.M., 1993, Genetic algorithms in optical design, in: Physics Computing '92, R.A. de Groot and J. Nadrchal (eds.) (World Scientific, Singapore) pp. 389-390.
9. Lucasius, C.B. and Kateman, G., 1993, Understanding and using genetic algorithms. Part 1. Concepts, properties and context. Chemometrics Intelligent Lab. Sys. 19, 1-33.
10. Lucasius, C.B. and Kateman, G., 1994, Understanding and using genetic algorithms. Part 2: Representation, configuration and hybridization. Chemometrics Intelligent Lab. Sys. 25, 99-145.
11. Lucasius, C.B. and Kateman, G., 1994, GATES toward evolutionary large-scale optimization: A software-oriented approach to genetic algorithms. Part 2. Toolbox description. Comput. Chem. 18(2), 137-156.
12. Meyer-Arendt, J.R., 1984, Introduction to Classical and Modern Optics, 2nd edition (Prentice-Hall, Englewood Cliffs, NJ).
13. Pedrotti, F.L. and L.S., 1987, Introduction to Optics (Prentice-Hall, Englewood Cliffs, NJ).
14. Rutten, H. and van Venrooij, M., 1988, Telescope Optics, Evaluation and Design (Willmann-Bell).
15. Spears, W.M. and De Jong, K.A., 1991, On the virtues of parameterized uniform crossover, in: Proceedings of the Fourth International Conference on Genetic Algorithms, R.K. Belew and L.B. Booker (eds.) (San Mateo, CA, Morgan Kaufmann) pp. 230-236.
16. Syswerda, G., 1989, Uniform crossover in genetic algorithms, in: Proceedings of the Third International Conference on Genetic Algorithms, J.D. Schaffer (ed.) (San Mateo, CA, Morgan Kaufmann) pp. 2-9.
17. Whitley, D., Mathias, K. and Fitzhorn, P., 1991, Delta coding: An iterative search strategy for genetic algorithms, in: Proceedings of the Fourth International Conference on Genetic Algorithms, R.K. Belew and L.B. Booker (eds.) (San Mateo, CA, Morgan Kaufmann) pp. 77-84.