Algorithms and concepts for robust optimization

Goerigk, Marc (2013) Algorithms and concepts for robust optimization. PhD thesis, UNSPECIFIED.

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Abstract

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.

Item Type:
Thesis (PhD)
ID Code:
76552
Deposited By:
Deposited On:
10 Nov 2015 09:52
Refereed?:
No
Published?:
Published
Last Modified:
01 Nov 2020 07:24