2010
DOI: 10.1016/j.ins.2010.05.001
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A swarm intelligence approach to the quadratic minimum spanning tree problem

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Cited by 102 publications
(33 citation statements)
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“…Therefore, only the inclusion of (2) is needed to obtain the complete RLT-1 reformulation. It was shown by Lee and Leung [17] that (5), (7), and (11) define facets of BQFP. In that study, it was also shown that the clique and the cut inequalities for BQP [16] also define facets for BQFP.…”
Section: Rlt-1 Based Boundsmentioning
confidence: 99%
“…Therefore, only the inclusion of (2) is needed to obtain the complete RLT-1 reformulation. It was shown by Lee and Leung [17] that (5), (7), and (11) define facets of BQFP. In that study, it was also shown that the clique and the cut inequalities for BQP [16] also define facets for BQFP.…”
Section: Rlt-1 Based Boundsmentioning
confidence: 99%
“…The frequently used MST searching algorithms are the Kruskal algorithm and the Prim algorithm [16][17][18]. Both of these two algorithms come from greedy ideas.…”
Section: Mst Searching Methodsmentioning
confidence: 99%
“…Pereira et al [7] proposed some new formulations using a particular partitioning of the spanning trees, and provided a new mixed binary formulation for the problem by applying the first level of the reformulation-linearization technique (RLT). The most effective heuristic approaches for the QMSTP can be found in [2,[8][9][10].…”
Section: Introductionmentioning
confidence: 99%