Multi-objective evolutionary optimization of computation-intensive simulations

Elmar Kiesling, Bernhard Grill, Andreas Ekelhart, Christian Stummer, Christine Strauss

Expensive fitness functions, such as simulations, pose a challenge in optimization scenarios. Despite the use of metaheuristic optimization algorithms, simulation-optimization problems hence do not necessarily converge within reasonable runtime. We outlined a number of approaches to tackle this issue and will continue our experiments with these and other techniques. Our goal is to reduce the number of required simulation replications and the runtime spent evaluating each candidate solution in the context of information security control selection.

Department of Accounting, Innovation and Strategy
External organisation(s)
Technische Universität Wien, Secure Business Austria (SBA), Universität Bielefeld
Publication date
Peer reviewed
Austrian Fields of Science 2012
102016 IT security, 502050 Business informatics, 101015 Operations research
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