Improved complexity bound for the maximum cardinality bottleneck bipartite matching problem
Discrete Applied Mathematics
Graph theory: An algorithmic approach (Computer science and applied mathematics)
Graph theory: An algorithmic approach (Computer science and applied mathematics)
Lexicographic bottleneck problems
Operations Research Letters
Bottleneck analysis for network flow model
Advances in Engineering Software
Committee selection with a weight constraint based on a pairwise dominance relation
ADT'11 Proceedings of the Second international conference on Algorithmic decision theory
On direct methods for lexicographic min-max optimization
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
Operations Research Letters
Lexicographic balanced optimization problems
Operations Research Letters
Multicriteria 0-1 knapsack problems with k-min objectives
Computers and Operations Research
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In combinatorial optimization, the bottleneck (or minmax) problems are those problems where the objective is to find a feasible solution such that its largest cost coefficient elements have minimum cost. Here we consider a generalization of these problems, where under a lexicographic rule we want to minimize the cost also of the second largest cost coefficient elements, then of the third largest cost coefficients, and so on. We propose a general rule which leads, given the considered problem, to a vectorial version of the solution procedure for the underlying sum optimization (minsum) problem. This vectorial procedure increases by a factor of k (where k is the number of different cost coefficients) the complexity of the corresponding sum optimization problem solution procedure.