Selecting Simulation Algorithm Portfolios by Genetic Algorithms

Ewald, Roland and Schulz, Rene and Uhrmacher, Adelinde M. (2010) Selecting Simulation Algorithm Portfolios by Genetic Algorithms. In: 24th ACM/IEEE/SCS Workshop on Principles of Advanced and Distributed Simulation (PADS 2010), 17-19 May 2010, Atlanta, Georgia, USA. Proceedings, published by IEEE, Print ISSN: 1087-4097, pp. 48-56.

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An algorithm portfolio is a set of algorithms that are bundled together for increased overall performance. While being mostly applied to computationally hard problems so far, we investigate portfolio selection for simulation algorithms and focus on their application to adaptive simulation replication. Since the portfolio selection problem is itself hard to solve, we introduce a genetic algorithm to select the most promising portfolios from large sets of simulation algorithms. The effectiveness of this mechanism is evaluated by data from both a realistic performance study and a dedicated test environment.

Item Type: Conference or Workshop Item (Paper)
Additional Information: doi:10.1109/PADS.2010.5471673
Projects: CoSa, GRK dIEM oSiRiS