Integer solution to synthesis of communication networks
Mathematics of Operations Research
Designing least-cost nonblocking broadband networks
Journal of Algorithms
A flexible model for resource management in virtual private networks
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Provisioning a virtual private network: a network design problem for multicommodity flow
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
TSP Cuts Which Do Not Conform to the Template Paradigm
Computational Combinatorial Optimization, Optimal or Provably Near-Optimal Solutions [based on a Spring School]
Simpler and better approximation algorithms for network design
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
A tight bound on approximating arbitrary metrics by tree metrics
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
A Factor 2 Approximation Algorithm for the Generalized Steiner Network Problem
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
Provisioning virtual private networks under traffic uncertainty
Networks - Special Issue on Multicommodity Flows and Network Design
New Approaches for Virtual Private Network Design
SIAM Journal on Computing
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Communication: Robust network optimization under polyhedral demand uncertainty is NP-hard
Discrete Applied Mathematics
Speeding up IP-based algorithms for constrained quadratic 0–1 optimization
Mathematical Programming: Series A and B - Series B - Special Issue: Combinatorial Optimization and Integer Programming
The VPN Problem with Concave Costs
SIAM Journal on Discrete Mathematics
Operations Research Letters
Models and algorithms for robust network design with several traffic scenarios
ISCO'12 Proceedings of the Second international conference on Combinatorial Optimization
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Modern life heavily relies on communication networks that operate efficiently. A crucial issue for the design of communication networks is robustness with respect to traffic fluctuations, since they often lead to congestion and traffic bottlenecks. In this paper, we address an NP-hard single commodity robust network design problem, where the traffic demands change over time. For k different times of the day, we are given for each node the amount of singlecommodity flow it wants to send or to receive. The task is to determine the minimum-cost edge capacities such that the flow can be routed integrally through the net at all times. We present an exact branch-and-cut algorithm, based on a decomposition into biconnected network components, a clever primal heuristic for generating feasible solutions from the linear-programming relaxation, and a general cutting-plane separation routine that is based on projection and lifting. By presenting extensive experimental results on realistic instances from the literature, we show that a suitable combination of these algorithmic components can solve most of these instances to optimality. Furthermore, cutting-plane separation considerably improves the algorithmic performance.