Hitting forbidden minors: Approximation and Kernelization

We study a general class of problems called F-deletion problems. In an F-deletion problem, we are asked whether a subset of at most $k$ vertices can be deleted from a graph $G$ such that the resulting graph does not contain as a minor any graph from the family F of forbidden minors. We obtain a number of algorithmic results on the F-deletion problem when F contains a planar graph. We give (1) a linear vertex kernel on graphs excluding $t$-claw $K_{1,t}$, the star with $t$ leves, as an induced subgraph, where $t$ is a fixed integer. (2) an approximation algorithm achieving an approximation ratio of $O(\log^{3/2} OPT)$, where $OPT$ is the size of an optimal solution on general undirected graphs. Finally, we obtain polynomial kernels for the case when F contains graph $\theta_c$ as a minor for a fixed integer $c$. The graph $\theta_c$ consists of two vertices connected by $c$ parallel edges. Even though this may appear to be a very restricted class of problems it already encompasses well-studied problems such as {\sc Vertex Cover}, {\sc Feedback Vertex Set} and Diamond Hitting Set. The generic kernelization algorithm is based on a non-trivial application of protrusion techniques, previously used only for problems on topological graph classes

A primal–dual interpretation of two 2-approximation algorithms for the feedback vertex set problem in undirected graphs

Recently, Becker and Geiger and Bafna, Berman and Fujito gave 2-approximation algorithms for the feedback vertex set problem in undirected graphs. We show how their algorithms can be explained in terms of the primal–dual method for approximation algorithms, which has been used to derive approximation algorithms for network design problems. In the process, we give a new integer programming formulation for the feedback vertex set problem whose integrality gap is at worst a factor of two; the well-known cycle formulation has an integrality gap of (log n), as shown by Even, Naor, Schieber and Zosin. We also give a new 2-approximation algorithm for the problem which is a simpli cation of the Bafna et al. algorithm

Half-integrality, LP-branching and FPT Algorithms

A recent trend in parameterized algorithms is the application of polytope tools (specifically, LP-branching) to FPT algorithms (e.g., Cygan et al., 2011; Narayanaswamy et al., 2012). However, although interesting results have been achieved, the methods require the underlying polytope to have very restrictive properties (half-integrality and persistence), which are known only for few problems (essentially Vertex Cover (Nemhauser and Trotter, 1975) and Node Multiway Cut (Garg et al., 1994)). Taking a slightly different approach, we view half-integrality as a \emph{discrete} relaxation of a problem, e.g., a relaxation of the search space from $\{0,1\}^V$ to $\{0,1/2,1\}^V$ such that the new problem admits a polynomial-time exact solution. Using tools from CSP (in particular Thapper and \v{Z}ivn\'y, 2012) to study the existence of such relaxations, we provide a much broader class of half-integral polytopes with the required properties, unifying and extending previously known cases. In addition to the insight into problems with half-integral relaxations, our results yield a range of new and improved FPT algorithms, including an $O^*(|\Sigma|^{2k})$-time algorithm for node-deletion Unique Label Cover with label set $\Sigma$ and an $O^*(4^k)$-time algorithm for Group Feedback Vertex Set, including the setting where the group is only given by oracle access. All these significantly improve on previous results. The latter result also implies the first single-exponential time FPT algorithm for Subset Feedback Vertex Set, answering an open question of Cygan et al. (2012). Additionally, we propose a network flow-based approach to solve some cases of the relaxation problem. This gives the first linear-time FPT algorithm to edge-deletion Unique Label Cover.Comment: Added results on linear-time FPT algorithms (not present in SODA paper

The minimum length corridor problem : exact, approximative and heuristic algorithms

Orientador: Cid Carvalho de SouzaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Esta dissertação tem como foco a investigação experimental de algoritmos exatos, aproximativos e heurísticos aplicados na resolução do chamado problema do corredor de comprimento mínimo (PCCM). No PCCM recebemos um polígono retilinear P e um conjunto de polígonos retilineares menores formando uma subdivisão S planar conexa de P. Uma solução para este problema, também chamada de corredor, é formada por um conjunto conexo de arestas de S, e tal que cada face interna em S possui pelo menos um ponto em sua borda que pertence a alguma aresta deste conjunto. O objetivo então é encontrar um corredor tal que a soma total dos comprimentos das arestas seja a menor possível. Trata-se de um problema NP-difícil com aplicações em áreas diversas, tais como telecomunicações, engenharia civil e projeto de circuitos VLSI. O PCCM pode ser reduzido polinomialmente a um problema em grafos denominado problema da árvore de Steiner com grupos (PASG). Considerando esta transformação, estudamos e implementamos dois métodos aproximativos, um método exato de branch-and-cut, e um método heurístico baseado na metaheurística GRASP combinada com um evolutionary path relinking (GRASP+EPR). Além disso, propomos três heurísticas de busca local que visam melhorar a qualidade de soluções do PASG. Instâncias do PCCM foram geradas aleatoriamente, nas quais aplicamos os métodos implementados. Analisamos os resultados, e apresentamos as situações onde é interessante utilizar cada método. Verificamos que o método branch-and-cut foi capaz de encontrar soluções ótimas para instâncias que julgamos ser de grande porte em tempos computacionalmente aceitáveis. O melhor algoritmo aproximativo obteve corredores que na média têm comprimento 17% maior que o comprimento ótimo. Se combinarmos este algoritmo com as heurísticas de melhoria propostas este percentual cai para a média de 3,5%. Finalmente, o GRASP+EPR consome mais tempo que este algoritmo aproximativo, entretanto, o comprimento dos corredores obtidos por ele é em média 0,9% maior que o comprimento ótimoAbstract: This dissertation focuses on the experimental investigation of exact, approximation and heuristic algorithms applied to solve the so-called minimum length corridor problem (MLCP). In the MLCP we receive a rectilinear polygon P and a set of minor rectilinear polygons forming a connected planar subdivision S of P. A solution for this problem, also called corridor, is formed by a set of connected edges of S, and such that each inner face of S has at least one point on its your border which belongs to an edge in this set. The goal is to find a corridor such that the sum of lengths of the edges is as small as possible. This is an NP-hard problem with applications in several areas such as telecommunications, civil engineering and design of VLSI circuits. The MLCP can be polynomially reduced to a graph problem known as group Steiner tree problem (GSTP). Based on this transformation, we studied and implemented two approximation methods, an exact branch-and-cut method, and a heuristic method based on the metaheuristic GRASP combined with an evolutionary path relinking (GRASP+EPR). Furthermore, we propose three local search heuristics to improve the quality of GSTP solutions. MLCP instances were randomly generated, in which we apply the methods implemented. We analyzed the results, and present situations where it is interesting to use each method. We found that the branch-and-cut has been able to find optimal solutions for instances that we consider to be large in acceptable computational times. The best approximation algorithm obtained corridors having average length 17% higher than the optimum length. If we combine this algorithm with the improvement heuristics proposed this percentage drops to an average of 3.5%. Finally, the GRASP+EPR spent more time than this approximation algorithm, however, the length of the corridors obtained by the method is, on average, 0.9% higher than the optimum lengthMestradoCiência da ComputaçãoMestre em Ciência da Computaçã