Modelling Some Robust Design Problems via Conic Optimization

Diah Chaerani () and Cornelis Roos ()
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Diah Chaerani: Delft University of Technology
Cornelis Roos: Delft University of Technology

A chapter in Operations Research Proceedings 2006, 2007, pp 209-214 from Springer

Abstract: Abstract In this paper, we deal with modelling robust design problems via conic optimization. A robust design problem deals with finding a robust optimal solution of an uncertain design problem. The uncertain data is assumed to belong to a so-called uncertainty set $$ \mathcal{U} $$ . Uncertainty means that the data is not known exactly at the time when the solution has to be determined. In order to find a robust optimal solution, we use the robust optimization (RO) methodology of Ben-Tal and Nemirovskii. We demonstrate this on the robust shortest path problem (RSPP), the robust maximum flow problem (RMFP) and the robust resistance network topology design (RNTD) problem.

Keywords: Convex Cone; Robust Optimization; Conic Optimization; Robust Counterpart; Ellipsoidal Uncertainty (search for similar items in EconPapers)
Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-540-69995-8_35

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DOI: 10.1007/978-3-540-69995-8_35

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