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@PHDTHESIS{Tieves:682215,
      author       = {Tieves, Martin},
      othercontributors = {Koster, Arie Marinus and Amaldi, Edoardo},
      title        = {{D}iscrete and robust optimization approaches to network
                      design with compression and virtual network embedding},
      school       = {RWTH Aachen University},
      type         = {Dissertation},
      address      = {Aachen},
      reportid     = {RWTH-2017-00724},
      pages        = {1 Online-Ressource (xi, 220 Seiten) : Diagramme, 1 Karte},
      year         = {2016},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University 2017; Dissertation, RWTH Aachen University, 2016},
      abstract     = {In this thesis, we study two optimization problems, the
                      Network Design Problem with Compression (NDPC) and the
                      Virtual Network Embedding Problem (VNE). In both cases, our
                      interest into the topic is motivated by the importance of
                      these problems within the telecommunication industry, where
                      they arise in the context of introducing new services and
                      technologies.Throughout this work, we employ concepts and
                      methods from the area of mathematical, respectively
                      combinatorial, optimization. We aim to provide new insights,
                      both from a theoretical and from a practical point of view.
                      For that purpose, we carry out extensive computational
                      experiments to strengthen our theoretical results. Wherever
                      possible, we put our results into context with the existing
                      literature.We follow a similar line of thought for both
                      problems. For the NDPC problem, we present a mixed integer
                      linear programming (MILP) formulation, detailed polyhedral
                      investigations, and considerations on the problems
                      computational complexity as well as a discussion on the
                      problem under data uncertainty. We conclude our work on NDPC
                      by computational results and an outlook into further
                      research directions.For the VNE problem, we also start with
                      an MILP formulation. We discuss heuristic problem approaches
                      and investigate the problem’s computational complexity in
                      great detail. We consider the VNE problem with data
                      uncertainty and develop exact and heuristic solution
                      approaches for this case. As for the NDPC problem, we
                      present extensive computational experiments to evaluate our
                      results. The chapter is closed by a short summary and a
                      brief introduction to future research topics.We conclude
                      this thesis by a final overview on the here presented
                      results and with some final remarks.},
      cin          = {113320 / 110000},
      ddc          = {510},
      cid          = {$I:(DE-82)113320_20140620$ / $I:(DE-82)110000_20140620$},
      typ          = {PUB:(DE-HGF)11},
      urn          = {urn:nbn:de:hbz:82-rwth-2017-007244},
      doi          = {10.18154/RWTH-2017-00724},
      url          = {https://publications.rwth-aachen.de/record/682215},
}