2016
DOI: 10.1016/j.endm.2016.11.011
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On Minimum Maximal Distance-k Matchings

Abstract: We study the computational complexity of several problems connected with finding a maximal distance-k matching of minimum cardinality or minimum weight in a given graph. We introduce the class of k-equimatchable graphs which is an edge analogue of k-equipackable graphs. We prove that the recognition of k-equimatchable graphs is co-NP-complete for any fixed k ≥ 2. We provide a simple characterization for the class of strongly chordal graphs with equal k-packing and k-domination numbers. We also prove that for a… Show more

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Cited by 6 publications
(5 citation statements)
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“…A distance-based extension of equimatchability was recently studied by Kartynnik and Ryzhikov [15]. In this paper we generalize the property of equimatchability of graphs in two further ways by introducing two graph parameters measuring how far a graph is from being equimatchable.…”
Section: Introductionmentioning
confidence: 99%
“…A distance-based extension of equimatchability was recently studied by Kartynnik and Ryzhikov [15]. In this paper we generalize the property of equimatchability of graphs in two further ways by introducing two graph parameters measuring how far a graph is from being equimatchable.…”
Section: Introductionmentioning
confidence: 99%
“…A graph G is called equimatchable if every maximal matching of G has the same cardinality. The structure of equimatchable graphs has been widely studied in the literature (see for instance [1,4,2,5,7,8,10,14,15,16]). The counterpart of equimatchable graphs for independent sets is called well-covered graphs: a graph is well-covered if all its maximal independent sets have the same size.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, a distance-2 matching is usually called an induced matching. These invariants have been studied in various papers and are closely related to many other concepts (see [1,2,6,7,8,9,11,12] for examples). The magnitude relation between the beans function B G (x) for a given value of x ≥ 1 and each of the two invariants will be explained in detail in Section 2.…”
Section: Introductionmentioning
confidence: 99%