Algorithms and concepts for robust optimization

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.

Name dc:type.qualificationname

Ph.D.

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

Georg-August Universität Göttingen

Year dc:date.issued

2013

Authors dc:creator

• Goerigk, Marc
• Schöbel, Anita
• Lübbecke, Marco