Friday, 10:30 - 10:55 h, Room: H 3503


Christian Raack
Cutset inequalities for robust network design


In order to create and operate resource- and cost-efficient networks the uncertainty of traffic demand (data, passengers) has to be taken into account already in the strategic capacity design process. A promising approach is robust optimization (RO).
Network design problems in telecommunications or public transport
are often solved using Mixed Integer Programming (MIP) models based on
multi-commodity-flow formulations. It is known that the solution
process can be sped up if strong valid inequalities based on network cuts, so-called cutset inequalities, are used as cutting planes.
In this work, combining methods from RO and MIP, we study the impact of cutset inequalities in solving robust network design problems.
We assume that traffic demands are given as a polyhedral set and
present facet proofs for different variants of these inequalities in
different variable spaces thereby generalizing the deterministic single scenario case. We show that robust cutset inequalities are independent of the chosen recourse scheme (static or dynamic routing). We also report on computational tests showing a significant speed-up for standard solvers such as CPLEX.


Talk 1 of the invited session Fri.1.H 3503
"Robust and survivable network design" [...]
Cluster 23
"Telecommunications & networks" [...]


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