Our first focus is the Capacitated Partition Vertex Cover (C-PVC) problem in hypergraphs. In C-PVC, we are given a hypergraph with capacities on its vertices and a partition of the hyperedge set into $ω$ distinct groups. The objective is to select a minimum size subset of vertices that satisfies two main conditions: (1) in each group, the total number of covered hyperedges meets a specified threshold, and (2) the number of hyperedges assigned to any vertex respects its capacity constraint. A covered hyperedge is required to be assigned to a selected vertex that belongs to the hyperedge. This formulation generalizes classical Vertex Cover, Partial Vertex Cover, and Partition Vertex Cover. We investigate two primary variants: soft capacitated (multiple copies of a vertex are allowed) and hard capacitated (each vertex can be chosen at most once). Let $f$ denote the rank of the hypergraph. Our main contributions are: $(i)$ an $(f+1)$-approximation algorithm for the weighted soft-capacitated C-PVC problem, which runs in $n^{O(ω)}$ time, and $(ii)$ an $(f+ε)$-approximation algorithm for the unweighted hard-capacitated C-PVC problem, which runs in $n^{O(ω/ε)}$ time. We also study a natural generalization of the edge cover problem, the \emph{Weighted Partition Edge Cover} (W-PEC) problem, where each edge has an associated weight, and the vertex set is partitioned into groups. For each group, the goal is to cover at least a specified number of vertices using incident edges, while minimizing the total weight of the selected edges. We present the first exact polynomial-time algorithm for the weighted case, improving runtime from $O(ωn^3)$ to $O(mn+n^2 \log n)$ and simplifying the algorithmic structure over prior unweighted approaches.
翻译:我们首先关注超图中的带容量划分顶点覆盖(C-PVC)问题。在C-PVC问题中,给定一个顶点带容量的超图,以及将超边集划分为$ω$个不同组别的划分方案。目标在于选择一个最小规模的顶点子集,使其满足两个主要条件:(1)在每个组别中,被覆盖的超边总数达到指定阈值;(2)分配给任意顶点的超边数量不超过其容量约束。被覆盖的超边必须分配给一个属于该超边的被选顶点。此模型推广了经典的顶点覆盖、部分顶点覆盖及划分顶点覆盖问题。我们研究两个主要变体:软容量(允许顶点重复选择)与硬容量(每个顶点至多被选择一次)。令$f$表示超图的秩。我们的主要贡献包括:$(i)$ 针对加权软容量C-PVC问题的$(f+1)$近似算法,其时间复杂度为$n^{O(ω)}$;$(ii)$ 针对无权硬容量C-PVC问题的$(f+ε)$近似算法,其时间复杂度为$n^{O(ω/ε)}$。我们还研究了边覆盖问题的自然推广——加权划分边覆盖(W-PEC)问题,其中每条边具有关联权重,且顶点集被划分为若干组别。对于每个组别,目标是通过关联边覆盖至少指定数量的顶点,同时最小化所选边的总权重。我们首次提出了加权情况下的精确多项式时间算法,将时间复杂度从$O(ωn^3)$改进至$O(mn+n^2 \log n)$,并简化了相较于先前无权方法的算法结构。