Automatic Algorithm Selection for Complex Simulation Problems

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Springer Science & Business Media, Nov 20, 2011 - Computers - 382 pages

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.

Roland Ewald analyzes and discusses existing approaches to solve the algorithm selection problem in the context of simulation. He introduces a framework for automatic simulation algorithm selection and describes its integration into the open-source modelling and simulation framework James II. Its selection mechanisms are able to cope with three situations: no prior knowledge is available, the impact of problem features on simulator performance is unknown, and a relationship between problem features and algorithm performance can be established empirically. The author concludes with an experimental evaluation of the developed methods.

 

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Contents

1 Introduction
1
Part I Background
16
Part II Methods and Implementation
116
Part III Examples and Conclusion
270
A Appendix
334
Bibliography
349
Index
376
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