Erratum to: Polyhedral approximation of ellipsoidal uncertainty sets via extended formulations: a computational case study

Bärmann, Andreas; Heidt, Andreas; Martín, Alexander; Pokutta, Sebastian; Thurner, Christoph

doi:10.1007/s10287-016-0269-y

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2018

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“…In [4] and [5] the authors adopt ellipsoidal uncertainty sets to solve robust network design problems. Compared to stochastic optimization, it has better computational tractability.…”

Section: Uncertainty Setmentioning

confidence: 99%

Solving the bifurcated and nonbifurcated robust network loading problem with k‐adaptive routing

2018

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We experiment an alternative routing scheme for the Robust Network Loading problem with demand uncertainty. Named k-adaptive, it is based on the fact that the decision-maker chooses k second-stage solutions and then commits to one of them only after realization of the uncertainty. This routing scheme, with its corresponding k-partition of the uncertainty set, is dynamically defined under an iterative method to sequentially improve the solution. The method has an inherent characteristic of multiplying the number of variables and constraints after each iteration, so that additional measures are introduced in the solution strategy in order to control time performance. We compare our k-adaptive results with the ones obtained through other routing schemes and also verify the effectiveness of the methods utilized using several realistic instances from SNDlib.

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“…In [4] and [5] the authors adopt ellipsoidal uncertainty sets to solve robust network design problems. Compared to stochastic optimization, it has better computational tractability.…”

Section: Uncertainty Setmentioning

confidence: 99%