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Weighted Upper Edge Cover: Complexity and Approximability

机译:加权上边盖:复杂性和近似性

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Optimization problems consist of either maximizing or minimizing an objective function. Instead of looking for a maximum solution (resp. minimum solution), one can find a minimum maximal solution (resp. maximum minimal solution). Such "flipping" of the objective function was done for many classical optimization problems. For example, Minimum Vertex Cover becomes Maximum Minimal Vertex Cover, Maximum Independent Set becomes Minimum Maximal Independent Set and so on. In this paper, we propose to study the weighted version of Maximum Minimal Edge Cover called Upper Edge Cover, a problem having application in genomic sequence alignment. It is well-known that Minimum Edge Cover is polynomial-time solvable and the "flipped" version is NP-hard, but constant approximable. We show that the weighted Upper Edge Cover is much more difficult than Upper Edge Cover because it is not O(1~(1/2-ε)) approximable, nor O(1/Δ~(1-ε)) in edge-weighted graphs of size n and maximum degree Δ respectively. Indeed, we give some hardness of approximation results for some special restricted graph classes such as bipartite graphs, split graphs and fc-trees. We counter-balance these negative results by giving some positive approximation results in specific graph classes.
机译:优化问题包括最大化或最小化目标函数。代替寻找最大解(分别为最小解),可以找到最小最大解(即最大最小解)。目标函数的这种“翻转”是针对许多经典的优化问题进行的。例如,“最小顶点覆盖”变为“最大最小顶点覆盖”,“最大独立集”变为“最小最大独立集”,依此类推。在本文中,我们建议研究称为上边缘覆盖的最大最小边缘覆盖的加权版本,该问题在基因组序列比对中具有应用。众所周知,最小边缘覆盖率是多项式时间可解的,而“翻转”版本是NP难解的,但常数是近似的。我们显示加权的上边缘覆盖比上边缘覆盖困难得多,因为它不是O(1 / n〜(1 /2-ε))近似的,也不是O(1 /Δ〜(1-ε))大小分别为n和最大度数Δ的边缘加权图。实际上,对于某些特殊的受限图类,例如二部图,分裂图和fc树,我们给出了近似结果的硬度。我们通过在特定图类中给出一些正近似结果来抵消这些负结果。

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