A recursive procedure to generate all cuts for 0-1 mixed integer programs
Mathematical Programming: Series A and B
The convex hull of two core capacitated network design problems
Mathematical Programming: Series A and B
Topological design of ring networks
Computers and Operations Research
The hop-limit approach for spare-capacity assignment in survivable networks
IEEE/ACM Transactions on Networking (TON)
Source sink flows with capacity installation in batches
Discrete Applied Mathematics
Restoration strategies and spare capacity requirements in self-healing ATM networks
IEEE/ACM Transactions on Networking (TON)
Network Design Using Cut Inequalities
SIAM Journal on Optimization
A Cutting Plane Algorithm for Multicommodity Survivable Network Design Problems
INFORMS Journal on Computing
SONET/SDH ring assignment with capacity constraints
Discrete Applied Mathematics - Special issue: Algorithmic aspects of communication
Bidirected and unidirected capacity installation in telecommunication networks
Discrete Applied Mathematics - International symposium on combinatorial optimisation
Designing capacitated survivable networks: polyhedral analysis and algorithms
Designing capacitated survivable networks: polyhedral analysis and algorithms
A Distributed Memetic Algorithm for the Routing and Wavelength Assignment Problem
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Design of Survivable Networks Using Three-and Four-Partition Facets
Operations Research
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We study the design of capacitated survivable networks using directed p-cycles. A p-cycle is a cycle with at least three arcs, used for rerouting disrupted flow during edge failures. Survivability of the network is accomplished by reserving sufficient slack on directed p-cycles so that if an edge fails, its flow can be rerouted along the p-cycles. We describe a model for designing capacitated survivable networks based on directed p-cycles. We motivate this model by comparing it with other means of ensuring survivability, and present a mixed-integer programming formulation for it. We derive valid inequalities for the model based on the minimum capacity requirement between partitions of the nodes and give facet conditions for them. We discuss the separation for these inequalities and present results of computational experiments for testing their effectiveness as cutting planes when incorporated in a branch-and-cut algorithm. Our experiments show that the proposed inequalities reduce the computational effort significantly.