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Robust optimization is an emerging field in telecommunication network design which takes future traffic uncertainty into account. This yields optimal robust network designs which are optimal for all traffic realizations within a pre-defined set of uncertainty. In 2003, Bertsimas and Sim have introduced an adjustable uncertainty set for general optimization problems preserving the computational complexity of the original non-robust problem. Recently, Koster et al. have applied this approach to network design problems. The authors investigate the importance of statistical input data analysis to determine reasonable parameter settings for robust network planning.
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