Publication: Optimization of telescope scheduling: algorithmic research and scientific policy
Loading...
Official URL
Full text at PDC
Publication Date
2003-05
Advisors (or tutors)
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
EDP Sciencies
Citations
Exportar
Abstract
The use of very expensive facilities in Modern Astronomy has demonstrated the importance of automatic modes in the operation of large telescopes. As a consequence, several mathematical tools have been applied and developed to solve the (NP - hard) scheduling optimization problem: from simple heuristics to the more complex genetic algorithms or neural networks. In this work, the basic scheduling problem is translated into mathematical language and two main methods are used to solve it: neighborhood search methods and genetic algorithms; both of them are analysed. It is shown that the algorithms are sensitive to the scientific policy by means of the definition of the objective function ( F) and also by the assignment of scientific priorities to the projects. The definition of F is not trivial and requires a detailed discussion among the Astronomical Community.
Description
UCM subjects
Unesco subjects
Keywords
Citation
Ball, M. O., Magnanti, T. L., Monma, C. L., & Nemhauser, G. L. (ed.) 1995, Network Models, Handbooks in Operations Research and Management Science 7 (Amsterdam: Elsevier Science B.V.)
Chelouah, R., & Siarry, P. 2000, J. Heuristics, 6, 191
Dasgupta, D., & Michalewicz, Z. (ed.) 1997, Evolutionary Algorithms in Engineering Applications (Springer Verlag, Inc. Berlin)
Drummond, M., Bresina, J., Swanson, K., Edgington,W.,& Henry, G. 1994, The Associate Principal Astronomer Telescope Operatios Model, Proc. in i-SATRAS 94
Ford, J. 1998, A report on SPIE’s International Symposium on Astronomical Telescopes and Instrumentation (URL: http://www.gb.nrao.edu/GBT/MC/doc/spie98/jford98tripreport/)
Garey, M. R., & Johnson, D. S. 1979, Computers and Intractability – A Guide to the Theory of NP-Completeness (New York: W. H. Freeman and Co.)
Gionnone, G., Chavan, A. M., Silva, D. R., Krueger, A. P., & Miller, G. E. 2000, in Astronomical Data Analysis Software and Systems IX, ed. N. Manset, C. Veillet,&D. Crabtree (San Francisco: ASP), ASP Conf. Ser., 216, 111
Holland, J. H. 1975, Adaptation in Natural and Artificial Systems (University of Michigan Press, Ann Arbor, MI, Internal Report)
Johnston, M. D., & Miller, G. E. 1994, in Intelligent Scheduling, ed. M. Zweben, &M. S. Fox (San Francisco: Morgan Kaufmann), 391
Johnston, M. D., & Adorf, H.-M. 1992, Computers Ops Res., 19 (3/4), 209
Manset, N., Veillet, C., & Crabtree, D. (ed.) 2000, Astronomical Data Analysis Software and System IX (San Francisco: ASP), ASP Conf. Ser., 216
Martínez, P., & Yáñez, J. 2002, Neural Networks, 15 (3), 363
Rayward-Smith, V. J., Osman, I. H., Reeves, C. R., & Smith, G. D. 1996, Modern Heuristic Search Methods (Chichester: John Wiley & Sons Ltd)
Reeves, C. R. (ed.) 1993, Modern Heuristic Techniques for Combinatorial Problems (Oxford: Blackwell Scientific Publications)