Decomposing Cubic Graphs into Connected Subgraphs of Size Three

Let $S=\{K_{1,3},K_3,P_4\}$ be the set of connected graphs of size 3. We study the problem of partitioning the edge set of a graph $G$ into graphs taken from any non-empty $S'\subseteq S$. The problem is known to be NP-complete for any possible choice of $S'$ in general graphs. In this paper, we assume that the input graph is cubic, and study the computational complexity of the problem of partitioning its edge set for any choice of $S'$. We identify all polynomial and NP-complete problems in that setting, and give graph-theoretic characterisations of $S'$-decomposable cubic graphs in some cases.Comment: to appear in the proceedings of COCOON 201

On the complexity of computing the kk-restricted edge-connectivity of a graph

The \emph{$k$-restricted edge-connectivity} of a graph $G$, denoted by $\lambda_k(G)$, is defined as the minimum size of an edge set whose removal leaves exactly two connected components each containing at least $k$ vertices. This graph invariant, which can be seen as a generalization of a minimum edge-cut, has been extensively studied from a combinatorial point of view. However, very little is known about the complexity of computing $\lambda_k(G)$. Very recently, in the parameterized complexity community the notion of \emph{good edge separation} of a graph has been defined, which happens to be essentially the same as the $k$-restricted edge-connectivity. Motivated by the relevance of this invariant from both combinatorial and algorithmic points of view, in this article we initiate a systematic study of its computational complexity, with special emphasis on its parameterized complexity for several choices of the parameters. We provide a number of NP-hardness and W[1]-hardness results, as well as FPT-algorithms.Comment: 16 pages, 4 figure

азбиение ребер двудольного графа на наименьшее число подграфов, изоморфных подграфам простого цикла порядка 4

In this paper, we study the computational complexity for a problem of partitioning the edge set of a bipartite graph into the minimal number of subgraphs isomorphic to those of a simple cycle of order 4 in special graph classes. This problem is NP-hard and finds application in organizing the distribution of network packets over communication channels in the process of transmission from one router to another. We develop an O(nlogn) algorithm for solving that problem in a class of n order trees. Intractable cases of the problem are identified.Изучается вычислительная сложность задачи разбиения ребер двудольного графа на наименьшее число подграфов, изоморфных подграфам простого цикла порядка 4, в специальных классах графов. Задача относится к числу NP-трудных и находит применение при организации распределения сетевых пакетов по каналам связи в процессе передачи от одного маршрутизатора к другому. Разработан алгоритм, решающий задачу в классе деревьев порядка n за время O(n log n). Выделены трудноразрешимые случаи задачи

Разбиение расщепляемого графа на порожденные подграфы, изоморфные цепи порядка 3

The study of the computational complexity of problems on graphs is an urgent problem. We show that the problem of deciding whether the vertex set of a given split graph of order 3n can be partitioned into induced subgraphs isomorphic to P3 is a polynomially solvable problem. We develop a polynomial-time algorithm based on the method of augmenting graphs. The developed efficient algorithm can be used for solving team formation problems.Установление вычислительной сложности задач на графах является актуальной проблемой. В настоящей работе рассматривается задача, в которой требуется определить, существует ли в заданном 3n-вершинном расщепляемом графе n попарно непересекающихся порожденных подграфов, изоморфных простой цепи порядка 3. Разработан полиномиальный алгоритм, который решает эту задачу. В его основе лежит техника увеличивающих подграфов. Алгоритм может найти применение при решении задач формирования команд

Counting Connected Partitions of Graphs

Motivated by the theorem of Gy\H ori and Lov\'asz, we consider the following problem. For a connected graph $G$ on $n$ vertices and $m$ edges determine the number $P(G,k)$ of unordered solutions of positive integers $\sum_{i=1}^k m_i = m$ such that every $m_i$ is realized by a connected subgraph $H_i$ of $G$ with $m_i$ edges such that $\cup_{i=1}^kE(H_i)=E(G)$. We also consider the vertex-partition analogue. We prove various lower bounds on $P(G,k)$ as a function of the number $n$ of vertices in $G$, as a function of the average degree $d$ of $G$, and also as the size $\mathrm{CMC}_r(G)$ of $r$-partite connected maximum cuts of $G$. Those three lower bounds are tight up to a multiplicative constant. We also prove that the number $\pi(G,k)$ of unordered $k$-tuples with $\sum_{i=1}^kn_i=n$, that are realizable by vertex partitions into $k$ connected parts of respective sizes $n_1,n_2,\dots,n_k$, is $\Omega(d^{k-1})$

Graph Partitioning in Connected Components with Minimum Size Constraints via Mixed Integer Programming

In this work, a graph partitioning problem in a fixed number of connected components is considered. Given an undirected graph with costs on the edges, the problem consists on partitioning the set of nodes into a fixed number of subsets with minimum size, where each subset induces a connected subgraph with minimal edge cost. Mixed Integer Programming formulations together with a variety of valid inequalities are demonstrated and implemented in a Branch & Cut framework. A column generation approach is also proposed for this problem with additional cuts. Finally, the methods are tested for several simulated instances and computational results are discussed.Comment: 14 pages, 1 figure, 2 table

On the computational tractability of a geographic clustering problem arising in redistricting

Redistricting is the problem of dividing a state into a number $k$ of regions, called districts. Voters in each district elect a representative. The primary criteria are: each district is connected, district populations are equal (or nearly equal), and districts are "compact". There are multiple competing definitions of compactness, usually minimizing some quantity. One measure that has been recently promoted by Duchin and others is number of cut edges. In redistricting, one is given atomic regions out of which each district must be built. The populations of the atomic regions are given. Consider the graph with one vertex per atomic region (with weight equal to the region's population) and an edge between atomic regions that share a boundary. A districting plan is a partition of vertices into $k$ parts, each connnected, of nearly equal weight. The districts are considered compact to the extent that the plan minimizes the number of edges crossing between different parts. Consider two problems: find the most compact districting plan, and sample districting plans under a compactness constraint uniformly at random. Both problems are NP-hard so we restrict the input graph to have branchwidth at most $w$. (A planar graph's branchwidth is bounded by its diameter.) If both $k$ and $w$ are bounded by constants, the problems are solvable in polynomial time. Assume vertices have weight~1. One would like algorithms whose running times are of the form $O(f(k,w) n^c)$ for some constant $c$ independent of $k$ and $w$, in which case the problems are said to be fixed-parameter tractable with respect to $k$ and $w$). We show that, under a complexity-theoretic assumption, no such algorithms exist. However, we do give algorithms with running time $O(c^wn^{k+1})$. Thus if the diameter of the graph is moderately small and the number of districts is very small, our algorithm is useable