As motivated in chapter 1 (p. 1), this thesis covers mechanisms to automatically select suitable simulation algorithms for complex simulation problems, i.e., problems for which simulator performance is hard to foresee. This chapter concludes the thesis. Section 11.1 summarizes the main methodological contributions, introduced in chapter 4 (p. 119) to chapter 8 (p. 247). Besides relating them to the concepts presented in chapter 2 (p. 19) and chapter 3 (p. 93), their relative merits and drawbacks are discussed by analyzing the results from the case studies (ch. 9, p. 273, and ch. 10, p. 303). A more succinct list of theses can be found in section A.1 (p. 335). Open questions and future research directions are detailed in section 11.2.


Performance Data Selection Mapping Algorithm Selection Simulation System Portfolio Selection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Vieweg+Teubner Verlag | Springer Fachmedien Wiesbaden GmbH 2012

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  • Roland Ewald

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