Optimization based Simulation Model Development: Solving Robustness Issues

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Debuse, Justin and Miah, Shah Jahan (2011) Optimization based Simulation Model Development: Solving Robustness Issues. In: 5th IEEE International Conference on Digital Ecosystems and Technologies. IEEE, Piscataway, N.J, pp. 133-137.


Mathematical models are becoming popular to represent biological systems. A mathematical model can be based upon existing knowledge from scientific literature, expert opinion, and field and laboratory studies. However, there are significant issues in model development including robustness. This study therefore examines how model quality can be improved automatically using optimization approaches. Specifically, we examine how a recently developed robust model of a forest pest species, with potential application in areas such as risk prediction, may have its robustness further increased using optimization. Digital eco-systems provide a powerful and broader methodological foundation and support for the implementation of optimization through application of the design science method.

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Proceedings of the 5th IEEE International Conference on
Digital Ecosystems and Technologies Daejeon Convention Centre (DCC), Daejeon, Korea 31st May 2011 - 3rd June 2011

Item type Book Section
URI https://vuir.vu.edu.au/id/eprint/9800
DOI https://doi.org/10.1109/DEST.2011.5936611
Official URL http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumb...
ISBN 9781457708725 (ISBN) 9781457708718 (ISBN) 2150-4946 (ISSN)
Subjects Historical > Faculty/School/Research Centre/Department > School of Management and Information Systems
Historical > FOR Classification > 0806 Information Systems
Keywords ResPubID22735, mathematical model, simulation, optimization
Citations in Scopus 1 - View on Scopus
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