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Algorithms and concepts for robust optimization

Research output: ThesisDoctoral Thesis

Publication date14/01/2013
Number of pages213
Awarding Institution
  • Georg-August Universität Göttingen
  • Schöbel, Anita, Supervisor, External person
  • Lübbecke, Marco, Supervisor, External person
Award date14/01/2013
Place of PublicationGöttingen
  • Georg-August-Universität Göttingen
<mark>Original language</mark>English


In this work we consider uncertain optimization problems where no probability distribution is known. We introduce the approaches RecFeas and RecOpt to such a robust optimization problem, using a location theoretic point of view, and discuss both theoretical and algorithmic aspects. We then consider both continuous and discrete problem applications of robust optimization: Linear programs from the Netlib benchmark set, and the aperiodic timetabling problem on the continuous side; intermodal load planning, Steiner trees, periodic timetabling, and timetable information on the discrete side. Finally, we present the software library ROPI as a framework for robust optimization with support for most established mixed-integer programming solvers.