The complexity of finding most vital arcs and nodes
The complexity of finding most vital arcs and nodes
Approximation algorithms for finding highly connected subgraphs
Approximation algorithms for NP-hard problems
On the robust shortest path problem
Computers and Operations Research
Routing, Flow, and Capacity Design in Communication and Computer Networks
Routing, Flow, and Capacity Design in Communication and Computer Networks
How to Pay, Come What May: Approximation Algorithms for Demand-Robust Covering Problems
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Extending Scope of Robust Optimization: Comprehensive Robust Counterparts of Uncertain Problems
Mathematical Programming: Series A and B
Mesh-based Survivable Transport Networks: Options and Strategies for Optical, MPLS, SONET and ATM Networking
Robust Combinatorial Optimization with Exponential Scenarios
IPCO '07 Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization
Two-Stage Robust Network Design with Exponential Scenarios
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
Approximation complexity of min-max (regret) versions of shortest path, spanning tree, and knapsack
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Most vital links and nodes in weighted networks
Operations Research Letters
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We study a new two-stage version of an s-t path problem, which we call adaptable robust connection path (ARCP). Given an undirected graph G=(V,E), two vertices s,t@?V and two integers f,r@?Z"+, ARCP asks to find a set S@?E of minimum cardinality which connects s and t, such that for any 'failure set' F@?E with |F|@?f, the set of edges S@?F can be completed to a set which connects s and t by adding at most r edges from E@?F. We show the problem is NP-hard, and there is no polynomial-time @a-approximation algorithm for the problem for @a