Finding the most vital edge with respect to minimum spanning tree in weighted graphs
Information Processing Letters
Verification and sensitivity analysis of minimum spanning trees in linear time
SIAM Journal on Computing
Efficient algorithms for finding the most vital edge of a minimum spanning tree
Information Processing Letters
The complexity of finding most vital arcs and nodes
The complexity of finding most vital arcs and nodes
Finding the k most vital edges in the minimum spanning tree problem
Parallel Computing
Increasing the weight of minimum spanning trees
Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
Applications of Path Compression on Balanced Trees
Journal of the ACM (JACM)
A minimum spanning tree algorithm with inverse-Ackermann type complexity
Journal of the ACM (JACM)
A faster computation of the most vital edge of a shortest path
Information Processing Letters
An optimal minimum spanning tree algorithm
Journal of the ACM (JACM)
Finding the k most vital edges with respect to minimum spanning trees for fixed k
Discrete Applied Mathematics
On Short Paths Interdiction Problems: Total and Node-Wise Limited Interdiction
Theory of Computing Systems
Sensitivity analysis of minimum spanning trees in sub-inverse-ackermann time
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
Critical edges/nodes for the minimum spanning tree problem: complexity and approximation
Journal of Combinatorial Optimization
Hi-index | 0.01 |
We study in this paper the problem of finding in a graph a subset of k edges whose deletion causes the largest increase in the weight of a minimum spanning tree. We propose for this problem an explicit enumeration algorithm whose complexity, when compared to the current best algorithm, is better for general k but very slightly worse for fixed k. More interestingly, unlike in the previous algorithms, we can easily adapt our algorithm so as to transform it into an implicit exploration algorithm based on a branch and bound scheme. We also propose a mixed integer programming formulation for this problem. Computational results show a clear superiority of the implicit enumeration algorithm both over the explicit enumeration algorithm and the mixed integer program.