Interval data minmax regret network optimization problems
Discrete Applied Mathematics
Simulated annealing algorithm for the robust spanning tree problem
Journal of Heuristics
The Robust Traveling Salesman Problem with Interval Data
Transportation Science
An approximation algorithm for interval data minmax regret combinatorial optimization problems
Information Processing Letters
A note on the selection of Benders’ cuts
Mathematical Programming: Series A and B - Series B - Special Issue: Combinatorial Optimization and Integer Programming
Exact and heuristic algorithms for the interval data robust assignment problem
Computers and Operations Research
A constraint satisfaction approach to the robust spanning tree problem with interval data
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
On the complexity of the robust spanning tree problem with interval data
Operations Research Letters
The robust spanning tree problem with interval data
Operations Research Letters
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The Minmax Regret Spanning Tree problem is studied in this paper. This is a generalization of the well-known Minimum Spanning Tree problem, which considers uncertainty in the cost function. Particularly, it is assumed that the cost parameter associated with each edge is an interval whose lower and upper limits are known, and the Minmax Regret is the optimization criterion. The Minmax Regret Spanning Tree problem is an NP-Hard optimization problem for which exact and heuristic approaches have been proposed. Several exact algorithms are proposed and computationally compared with the most effective approaches of the literature. It is shown that a proposed branch-and-cut approach outperforms the previous approaches when considering several classes of instances from the literature.