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We describe the information system that has been built for the support sanitary teams. The system is aimed at supporting analytical work which must be carried out when there is a risk of epidemic outbreak. It is meant to provide tools for predicting the size of an epidemic on the basis of the actual data collected during its course. Since sanitary teams try to control the size of the epidemics such a tool must model also sanitary teams activities. As a result a model for the prediction can be quite complicated in terms of the number of equations it contains. Furthermore, since a model is based on several parameters there must be a tool for finding these parameters on the basis on the actual data corresponding to the epidemic evolution. The paper describes the proposition of such a system. It presents, in some details, the main components of the system. In particular, the environment for building complex models (containing not only the epidemic model but also activities of sanitary teams trying to inhibit the epidemic) is discussed. Then, the module for a model calibration is presented. The module is a part of server for solving optimal control problems and can be accessed via Internet. Finally, we show how optimal control problems can be constructed with the aim of the efficient epidemic management. Some optimal control problems related to that issue are discussed and numerical results of its solution are presented.
Czasopismo
Rocznik
Tom
Strony
393--406
Opis fizyczny
Bibliogr. 17 poz., rys.
Twórcy
autor
- Institute of Automatic Control and Robotics, Warsaw University of Technology, Sw. Andrzeja Boboli, 02-525 Warsaw, Poland
autor
- Institute of Automatic Control and Robotics, Warsaw University of Technology, Sw. Andrzeja Boboli, 02-525 Warsaw, Poland
autor
- Institute of Automatic Control and Robotics, Warsaw University of Technology, Sw. Andrzeja Boboli, 02-525 Warsaw, Poland
autor
- Faculty of Cybernetics Military University of Technology, Kaliskiego 2, 00-908 Warsaw, Poland
Bibliografia
- 1. Pytlak, R., Tarnawski, T., Fajdek, B., Stachura, M., (2013), Interactive Dynamic Optimization Server (IDOS) - Connecting one Modeling Language with Many Solvers, Optimization Methods & Solvers, in print.
- 2. Anderson, R.M., May, editors, (1991), Infectious Diseases of Humans: Dynamics and Control, Oxford University Press, Oxford.
- 3. Bailey, N.T.J, (1975), “The Mathematical Theory of Infectious Diseases”, Griffin, London.
- 4. Fruwirth T., Abdennadher S., (2003) Essentials of constraint programming, Springer.
- 5. Kermack, W.O. , McKendrick, A.G., (1927), Contributions to the mathematical theory of epidemics, Proc. R. Soc. Lond., A 1927, 115: 700-721.
- 6. Kermack, W.O. , McKendrick, A.G., (1932), Contributions to the mathematical theory of epidemics, Proc. R. Soc. Lond., A 1932, 138: 55-83.
- 7. Kermack, W.O. , McKendrick, A.G., (1933), Contributions to the mathematical theory of epidemics, Proc. R. Soc. Lond., A 1933, 141: 94-122.
- 8. Murray, J.D., (1993), Mathematical biology. I. An introduction, Springer-Verlag, Berlin, Heidelberg, New York.
- 9. Murray, J.D., (2001), Mathematical biology. II. Spatial models, Springer-Verlag, Berlin, Heidelberg, New York.
- 10. Pytlak, R., (1999), Numerical Methods for Optimal Control Problems with State Constraints, Lecture Notes in Mathematics 1707, Springer-Verlag.
- 11. Sterman, J.D., (2000), Business Dynamics, McGraw-Hill.
- 12. Modelon AB, Modelica, (2012), „JModelica User’s Guide“ v.1.8.
- 13. Wachter, A., (2002), An Interior Point Algorithm for Large-Scale Nonlinear Optimization with Applications in Process Engineering, PhD thesis, Carnegie Mellon University, Pittsburgh, PA, USA.
- 14. Wachter, A., (2010), An introduction to Ipopt: A tutorial for downloading, installing, and using Ipopt.
- 15. Wallace M., (2005), Hybrid algorithms, local search and ECLiPSe, CP Summer School
- 16. Wallace M., Schimpf J., (2002), Finding the right hybrid algorithm - A combinatorial meta-problem, Annals of Mathematics and Artificial Intelligence 34: 259-269.
- 17. Zawadzki, T., Pytlak, R., (2011), Extending System Dynamics Approach to Higher Index DAE’s, Proceedings of the System Dynamics Society 2011 Conference, July 24 -26.
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-f2dc1591-fe84-4f4b-8133-76ae80b9b467
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