Given a graph @math , a non-negative integer @math , and a weight function that maps each vertex in @math to a positive real number, the is about finding a maximum weighted independent set in @math of cardinality at most @math . A special case of MWBIS, when the weight assigned to each vertex is equal to its degree in @math , is called the problem. In other words, the MIVC problem is about finding an independent set of cardinality at most @math with maximum coverage. Since it is a generalization of the well-known Maximum Weighted Independent Set (MWIS) problem, MWBIS too does not have any constant factor polynomial time approximation algorithm assuming @math . In this paper, we study MWBIS in the context of bipartite graphs. We show that, unlike MWIS, the MIVC (and thereby the MWBIS) problem in bipartite graphs is NP-hard. Then, we show that the MWBIS problem admits a @math -factor approximation algorithm in the class of bipartite graphs, which matches the integrality gap of a natural LP relaxation.
A more general problem (also known by the same name, MWBIS,) was introduced and studied in the context of special graphs like trees, forests, cycle graphs, interval graphs, and planar graphs in @cite_9 where each vertex in the given graph @math has a cost associated with it and the problem is about finding an independent set of total cost at most @math (, where @math is a part of the input,) in @math that has the highest weight amongst all such independent sets. Apart from this work, to the best of our knowledge, not much is known about MWBIS.
@cite_9
1863224559 1998375208 1556146035 2007985221
We study a natural extension of the Maximum Weight Independent Set Problem (MWIS), one of the most studied optimization problems in Graph algorithms. We are given a graph @math , a weight function @math , a budget function @math , and a positive integer @math . The weight (resp. budget) of a subset of vertices is the sum of weights (resp. budgets) of the vertices in the subset. A @math -budgeted independent set in @math is a subset of vertices, such that no pair of vertices in that subset are adjacent, and the budget of the subset is at most @math . The goal is to find a @math -budgeted independent set in @math such that its weight is maximum among all the @math -budgeted independent sets in @math . We refer to this problem as MWBIS. Being a generalization of MWIS, MWBIS also has several applications in Scheduling, Wireless networks and so on. Due to the hardness results implied from MWIS, we study the MWBIS problem in several special classes of graphs. We design exact algorithms for trees, forests, cycle graphs, and interval graphs. In unweighted case we design an approximation algorithm for @math -claw free graphs whose approximation ratio ( @math ) is competitive with the approximation ratio ( @math ) of MWIS (unweighted). Furthermore, we extend Baker's technique Baker83 to get a PTAS for MWBIS in planar graphs. In the Maximum Weight Independent Set of Rectangles (MWISR) problem we are given a set of n axis-parallel rectangles in the 2D-plane, and the goal is to select a maximum weight subset of pairwise non-overlapping rectangles. Due to many applications, e.g. in data mining, map labeling and admission control, the problem has received a lot of attention by various research communities. We present the first (1 + e)-approximation algorithm for the MWISR problem with quasipolynomial running time 2poly(log n e). In contrast, the best known polynomial time approximation algorithms for the problem achieve superconstant approximation ratios of O(log log n) (unweighted case) and O(log n log log n) (weighted case). Key to our results is a new geometric dynamic program which recursively subdivides the plane into polygons of bounded complexity. We provide the technical tools that are needed to analyze its performance. In particular, we present a method of partitioning the plane into small and simple areas such that the rectangles of an optimal solution are intersected in a very controlled manner. Together with a novel application of the weighted planar graph separator theorem due to [4] this allows us to upper bound our approximation ratio by 1 + e. Our dynamic program is very general and we believe that it will be useful for other settings. In particular, we show that, when parametrized properly, it provides a polynomial time (1 + e)-approximation for the special case of the MWISR problem when each rectangle is relatively large in at least one dimension. Key to this analysis is a method to tile the plane in order to approximately describe the topology of these rectangles in an optimal solution. This technique might be a useful insight to design better polynomial time approximation algorithms or even a PTAS for the MWISR problem. In particular, note that our results imply that the MWISR problem is not APX-hard, unless NP ⊆ DTIME(2polylog (n)). Producing optimal left-deep trees is known to be NP-complete for general join graphs and a quite complex cost function counting disk accesses for a special block-wise nested-loop join [2]. Independent of any cost function is the dynamic programming approach to join ordering. The number of alternatives this approach generates is known as well [5]. Further, it is known that for some cost functions — those fulfilling the ASI property [4] — the problem can be solved in polynomial time for acyclic query graph, i.e., tree queries [2, 3]. We study the recently introduced Connected Feedback Vertex Set (CFVS) problem from the view-point of parameterized algorithms. CFVS is the connected variant of the classical Feedback Vertex Set problem and is defined as follows: given a graph G=(V,E) and an integer k, decide whether there exists F?V, |F|?k, such that G[V?F] is a forest and G[F] is connected. We show that Connected Feedback Vertex Set can be solved in time O(2 O(k) n O(1)) on general graphs and in time @math on graphs excluding a fixed graph H as a minor. Our result on general undirected graphs uses, as a subroutine, a parameterized algorithm for Group Steiner Tree, a well studied variant of Steiner Tree. We find the algorithm for Group Steiner Tree of independent interest and believe that it could be useful for obtaining parameterized algorithms for other connectivity problems.