|Title of PhD thesis:||Automatic Algorithm Selection for Complex Simulation Problems|
|Reviewers:||Adelinde M. Uhrmacher, University of Rostock, Rostock, Germany|
|David M. Nicol, University of Illinois at Urbana-Champaign, USA|
|Georgois K. Theodoropoulos, University of Birmingham, UK|
To select the most suitable simulation algorithm for a given task is often difficult. This is due to intricate interactions between model features, implementation details, and runtime environment, which may strongly affect the overall performance. An automated selection of simulation algorithms supports users in setting up simulation experiments, without demanding expert knowledge on simulation.
The first part of the thesis surveys existing approaches to solve the algorithm selection problem and discusses techniques to analyze simulation algorithm performance. A unified categorization of existing algorithm selection techniques is worked out, as these stem from various research domains (e.g., finance, artificial intelligence).
The second part introduces a software framework for automatic simulation algorithm selection and describes its constituents, as well as their integration into the modeling and simulation framework JAMES II. The implemented selection mechanisms are able to cope with three situations: a) no prior knowledge is available, b) the impact of problem features on performance is unknown, and c) a relationship between problem features and algorithm performance can be established empirically.
An experimental evaluation of the developed methods concludes the thesis. It is shown that an automated algorithm selection may significantly increase the overall performance of a simulation system. Some of the presented mechanisms also support the research on simulation methods, as they facilitate their development and evaluation.
- Roland Ewald, Stefan Leye and Adelinde M. Uhrmacher (2009): An Efficient and Adaptive Mechanism for Parallel Simulation Replication. - In: Proceedings of the 23rd ACM/IEEE/SCS Workshop on Principles of Advanced and Distributed Simulation (PADS 2009), pp. 104-113, IEEE Conference Publishing Services.
- Roland Ewald, Adelinde Uhrmacher and Kaustav Saha (2009): Data Mining for Simulation Algorithm Selection. - In: Proceedings of the SIMUTools'09: 2nd International Conference on Simulation Tools and Techniques.
- Roland Ewald, Jan Himmelspach, Matthias Jeschke, Stefan Leye and Adelinde M. Uhrmacher (2010): Flexible Experimentation in the Modeling and Simulation Framework JAMES II – Implications for Computational Systems Biology. - Briefings in Bioinformatics, 11(3):290-300.
- Roland Ewald, René Schulz and Adelinde M. Uhrmacher (2010): Selecting Simulation Algorithm Portfolios by Genetic Algorithms. - In: IEEE Workshop on Principles of Advanced and Distributed Simulation (PADS), pp. 48-56, IEEE, Piscataway, NJ, IEEE CPS.
- Matthias Jeschke and Roland Ewald (2008): Large-Scale Design Space Exploration of SSA. - In: Computational Methods in Systems Biology, vol. Volume 5307/2008, pp. 211-230, Springer Berlin / Heidelberg. Lecture Notes in Computer Science.