The Orderly Colored Longest Path Problem – Asurveyofapplicationsandnew Algorithms
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How Tough Is Toughness?
How tough is toughness? Hajo Broersma ∗ Abstract We survey results and open problems related to the toughness of graphs. 1 Introduction The concept of toughness was introduced by Chvátal [34] more than forty years ago. Toughness resembles vertex connectivity, but is different in the sense that it takes into account what the effect of deleting a vertex cut is on the number of resulting components. As we will see, this difference has major consequences in terms of computational complexity and on the implications with respect to cycle structure, in particular the existence of Hamilton cycles and k-factors. 1.1 Preliminaries We start with a number of crucial definitions and observations. Throughout this paper we only consider simple undirected graphs. Let G = (V; E) be such a graph. Every subset S ⊆ V induces a subgraph of G, denoted by G[S ], consisting of S and all edges of G between pairs of vertices of S . We use !(G) to denote the number of components of G, i.e., the set of maximal (with respect to vertex set inclusion) connected induced subgraphs of G.A vertex cut of G is a set S ⊂ V with !(G − S ) > 1. Clearly, complete graphs (in which every pair of vertices is joined by an edge) do not admit vertex cuts, but non-complete graphs have at least one vertex cut (if u and v are nonadjacent vertices in G, then the set S = V nfu; vg is a vertex cut such that !(G−S ) = 2). As usual, the (vertex) connectivity of G, denoted by κ(G), is the cardinality of a smallest vertex cut of G (if G is non-complete; for the complete graph Kn on n vertices it is usually set at n − 1). -
On Computing Longest Paths in Small Graph Classes
On Computing Longest Paths in Small Graph Classes Ryuhei Uehara∗ Yushi Uno† July 28, 2005 Abstract The longest path problem is to find a longest path in a given graph. While the graph classes in which the Hamiltonian path problem can be solved efficiently are widely investigated, few graph classes are known to be solved efficiently for the longest path problem. For a tree, a simple linear time algorithm for the longest path problem is known. We first generalize the algorithm, and show that the longest path problem can be solved efficiently for weighted trees, block graphs, and cacti. We next show that the longest path problem can be solved efficiently on some graph classes that have natural interval representations. Keywords: efficient algorithms, graph classes, longest path problem. 1 Introduction The Hamiltonian path problem is one of the most well known NP-hard problem, and there are numerous applications of the problems [17]. For such an intractable problem, there are two major approaches; approximation algorithms [20, 2, 35] and algorithms with parameterized complexity analyses [15]. In both approaches, we have to change the decision problem to the optimization problem. Therefore the longest path problem is one of the basic problems from the viewpoint of combinatorial optimization. From the practical point of view, it is also very natural approach to try to find a longest path in a given graph, even if it does not have a Hamiltonian path. However, finding a longest path seems to be more difficult than determining whether the given graph has a Hamiltonian path or not. -
Vertex Deletion Problems on Chordal Graphs∗†
Vertex Deletion Problems on Chordal Graphs∗† Yixin Cao1, Yuping Ke2, Yota Otachi3, and Jie You4 1 Department of Computing, Hong Kong Polytechnic University, Hong Kong, China [email protected] 2 Department of Computing, Hong Kong Polytechnic University, Hong Kong, China [email protected] 3 Faculty of Advanced Science and Technology, Kumamoto University, Kumamoto, Japan [email protected] 4 School of Information Science and Engineering, Central South University and Department of Computing, Hong Kong Polytechnic University, Hong Kong, China [email protected] Abstract Containing many classic optimization problems, the family of vertex deletion problems has an important position in algorithm and complexity study. The celebrated result of Lewis and Yan- nakakis gives a complete dichotomy of their complexity. It however has nothing to say about the case when the input graph is also special. This paper initiates a systematic study of vertex deletion problems from one subclass of chordal graphs to another. We give polynomial-time algorithms or proofs of NP-completeness for most of the problems. In particular, we show that the vertex deletion problem from chordal graphs to interval graphs is NP-complete. 1998 ACM Subject Classification F.2.2 Analysis of Algorithms and Problem Complexity, G.2.2 Graph Theory Keywords and phrases vertex deletion problem, maximum subgraph, chordal graph, (unit) in- terval graph, split graph, hereditary property, NP-complete, polynomial-time algorithm Digital Object Identifier 10.4230/LIPIcs.FSTTCS.2017.22 1 Introduction Generally speaking, a vertex deletion problem asks to transform an input graph to a graph in a certain class by deleting a minimum number of vertices. -
Solution of the Knight's Hamiltonian Path Problem on Chessboards
CORE Metadata, citation and similar papers at core.ac.uk Provided by Elsevier - Publisher Connector DISCRETE APPLIED MATHEMATICS ELSEVIER Discrete Applied Mathematics 50 (1994) 125-134 Solution of the knight’s Hamiltonian path problem on chessboards Axe1 Conrad”, Tanja Hindrichsb, Hussein MorsyC, Ingo WegenerdV* “Hiilsenbusch 27, 5632 Wermelskirchen I, Germany bPlettenburg 5, 5632 Wermelskirchen 2, Germany ‘BeckbuschstraJe 7, 4000 Diisseldorf 30, Germany dFB Informatik, LS II. University of Dortmund, Postfach 500500, 4600 Dortmund 50, Germany Received 17 June 1991; revised 12 December 1991 Abstract Is it possible for a knight to visit all squares of an n x n chessboard on an admissible path exactly once? The answer is yes if and only if n > 5. The kth position in such a path can be computed with a constant number of arithmetic operations. A Hamiltonian path from a given source s to a given terminal t exists for n > 6 if and only if some easily testable color criterion is fulfilled. Hamiltonian circuits exist if and only if n 2 6 and n is even. 1. Introduction In many textbooks on algorithmic methods two chess problems are presented as examples for backtracking algorithms: _ is it possible to place n queens on an n x n chessboard such that no one threatens another? - is it possible for a knight to visit all squares of an n x n cheesboard on an admissible path exactly once? Both problems are special cases of NP-complete graph problems, namely the maximal independent set problem and the Hamiltonian path problem (see [4]). We consider the second problem. -
Approximating the Maximum Clique Minor and Some Subgraph Homeomorphism Problems
Approximating the maximum clique minor and some subgraph homeomorphism problems Noga Alon1, Andrzej Lingas2, and Martin Wahlen2 1 Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv. [email protected] 2 Department of Computer Science, Lund University, 22100 Lund. [email protected], [email protected], Fax +46 46 13 10 21 Abstract. We consider the “minor” and “homeomorphic” analogues of the maximum clique problem, i.e., the problems of determining the largest h such that the input graph (on n vertices) has a minor isomorphic to Kh or a subgraph homeomorphic to Kh, respectively, as well as the problem of finding the corresponding subgraphs. We term them as the maximum clique minor problem and the maximum homeomorphic clique problem, respectively. We observe that a known result of Kostochka and √ Thomason supplies an O( n) bound on the approximation factor for the maximum clique minor problem achievable in polynomial time. We also provide an independent proof of nearly the same approximation factor with explicit polynomial-time estimation, by exploiting the minor separator theorem of Plotkin et al. Next, we show that another known result of Bollob´asand Thomason √ and of Koml´osand Szemer´ediprovides an O( n) bound on the ap- proximation factor for the maximum homeomorphic clique achievable in γ polynomial time. On the other hand, we show an Ω(n1/2−O(1/(log n) )) O(1) lower bound (for some constant γ, unless N P ⊆ ZPTIME(2(log n) )) on the best approximation factor achievable efficiently for the maximum homeomorphic clique problem, nearly matching our upper bound. -
Parameterized Edge Hamiltonicity
Parameterized Edge Hamiltonicity Michael Lampis1;?, Kazuhisa Makino1, Valia Mitsou2;??, Yushi Uno3 1 Research Institute for Mathematical Sciences, Kyoto University mlampis,[email protected] 2 CUNY Graduate Center [email protected] 3 Department of Mathematics and Information Sciences, Graduate School of Science, Osaka Prefecture University [email protected] Abstract. We study the parameterized complexity of the classical Edge Hamiltonian Path problem and give several fixed-parameter tractabil- ity results. First, we settle an open question of Demaine et al. by showing that Edge Hamiltonian Path is FPT parameterized by vertex cover, and that it also admits a cubic kernel. We then show fixed-parameter tractability even for a generalization of the problem to arbitrary hyper- graphs, parameterized by the size of a (supplied) hitting set. We also consider the problem parameterized by treewidth or clique-width. Sur- prisingly, we show that the problem is FPT for both of these standard parameters, in contrast to its vertex version, which is W-hard for clique- width. Our technique, which may be of independent interest, relies on a structural characterization of clique-width in terms of treewidth and complete bipartite subgraphs due to Gurski and Wanke. 1 Introduction The focus of this paper is the Edge Hamiltonian Path problem, which can be defined as follows: given an undirected graph G(V; E), does there exist a permutation of E such that every two consecutive edges in the permutation share an endpoint? This is a very well-known graph-theoretic problem, which corresponds to the restriction of (vertex) Hamiltonian Path to line graphs. -
Downloaded the Biochemical Pathways Information from the Saccharomyces Genome Database (SGD) [29], Which Contains for Each Enzyme of S
Algorithms 2015, 8, 810-831; doi:10.3390/a8040810 OPEN ACCESS algorithms ISSN 1999-4893 www.mdpi.com/journal/algorithms Article Finding Supported Paths in Heterogeneous Networks y Guillaume Fertin 1;*, Christian Komusiewicz 2, Hafedh Mohamed-Babou 1 and Irena Rusu 1 1 LINA, UMR CNRS 6241, Université de Nantes, Nantes 44322, France; E-Mails: [email protected] (H.M.-B.); [email protected] (I.R.) 2 Institut für Softwaretechnik und Theoretische Informatik, Technische Universität Berlin, Berlin D-10587, Germany; E-Mail: [email protected] y This paper is an extended version of our paper published in the Proceedings of the 11th International Symposium on Experimental Algorithms (SEA 2012), Bordeaux, France, 7–9 June 2012, originally entitled “Algorithms for Subnetwork Mining in Heterogeneous Networks”. * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +33-2-5112-5824. Academic Editor: Giuseppe Lancia Received: 17 June 2015 / Accepted: 29 September 2015 / Published: 9 October 2015 Abstract: Subnetwork mining is an essential issue in the analysis of biological, social and communication networks. Recent applications require the simultaneous mining of several networks on the same or a similar vertex set. That is, one searches for subnetworks fulfilling different properties in each input network. We study the case that the input consists of a directed graph D and an undirected graph G on the same vertex set, and the sought pattern is a path P in D whose vertex set induces a connected subgraph of G. In this context, three concrete problems arise, depending on whether the existence of P is questioned or whether the length of P is to be optimized: in that case, one can search for a longest path or (maybe less intuitively) a shortest one. -
On the Universal Near Shortest Simple Paths Problem
On the Universal Near Shortest Simple Paths Problem Luca E. Sch¨afer∗, Andrea Maier, Stefan Ruzika Department of Mathematics, Technische Universit¨at Kaiserslautern, 67663 Kaiserslautern, Germany Abstract This article generalizes the Near Shortest Paths Problem introduced by Byers and Waterman in 1984 using concepts of the Universal Shortest Path Prob- lem established by Turner and Hamacher in 2011. The generalization covers a variety of shortest path problems by introducing a universal weight vector. We apply this concept to the Near Shortest Paths Problem in a way that we are able to enumerate all universal near shortest simple paths. We present two recursive algorithms to compute the set of universal near shortest simple paths between two prespecified vertices and evaluate the running time com- plexity per path enumerated with respect to different values of the universal weight vector. Further, we study the cardinality of a minimal complete set with respect to different values of the universal weight vector. Keywords: Near shortest Paths, Dynamic Programming, Universal Shortest Path, Complexity, Enumeration 1. Introduction The K-shortest path problem is a well-studied generalization of the shortest path problem, where one aims to determine not only the shortest path, but arXiv:1906.05101v2 [math.CO] 23 Aug 2019 also the K shortest paths (K > 1) between a source vertex s and a sink vertex t. In contrast to the K-shortest path problem and its applications, (cf. [2, 7, 14, 24]), the near shortest paths problem, i.e., NSPP, received fewer attention in the literature, (cf. [3, 4, 23]). The NSPP aims to enumerate all ∗Corresponding author Email addresses: [email protected] (Luca E. -
Introducing Subclasses of Basic Chordal Graphs
Introducing subclasses of basic chordal graphs Pablo De Caria 1 Marisa Gutierrez 2 CONICET/ Universidad Nacional de La Plata, Argentina Abstract Basic chordal graphs arose when comparing clique trees of chordal graphs and compatible trees of dually chordal graphs. They were defined as those chordal graphs whose clique trees are exactly the compatible trees of its clique graph. In this work, we consider some subclasses of basic chordal graphs, like hereditary basic chordal graphs, basic DV and basic RDV graphs, we characterize them and we find some other properties they have, mostly involving clique graphs. Keywords: Chordal graph, dually chordal graph, clique tree, compatible tree. 1 Introduction 1.1 Definitions For a graph G, V (G) is the set of its vertices and E(G) is the set of its edges. A clique is a maximal set of pairwise adjacent vertices. The family of cliques of G is denoted by C(G). For v ∈ V (G), Cv will denote the family of cliques containing v. All graphs considered will be assumed to be connected. A set S ⊆ V (G) is a uv-separator if vertices u and v are in different connected components of G−S. It is minimal if no proper subset of S has the 1 Email: [email protected] aaURL: www.mate.unlp.edu.ar/~pdecaria 2 Email: [email protected] same property. S is a minimal vertex separator if there exist two nonadjacent vertices u and v such that S is a minimal uv-separator. S(G) will denote the family of all minimal vertex separators of G. -
On Digraph Width Measures in Parameterized Algorithmics (Extended Abstract)
On Digraph Width Measures in Parameterized Algorithmics (extended abstract) Robert Ganian1, Petr Hlinˇen´y1, Joachim Kneis2, Alexander Langer2, Jan Obdrˇz´alek1, and Peter Rossmanith2 1 Faculty of Informatics, Masaryk University, Brno, Czech Republic {xganian1,hlineny,obdrzalek}@fi.muni.cz 2 Theoretical Computer Science, RWTH Aachen University, Germany {kneis,langer,rossmani}@cs.rwth-aachen.de Abstract. In contrast to undirected width measures (such as tree- width or clique-width), which have provided many important algo- rithmic applications, analogous measures for digraphs such as DAG- width or Kelly-width do not seem so successful. Several recent papers, e.g. those of Kreutzer–Ordyniak, Dankelmann–Gutin–Kim, or Lampis– Kaouri–Mitsou, have given some evidence for this. We support this di- rection by showing that many quite different problems remain hard even on graph classes that are restricted very beyond simply having small DAG-width. To this end, we introduce new measures K-width and DAG- depth. On the positive side, we also note that taking Kant´e’s directed generalization of rank-width as a parameter makes many problems fixed parameter tractable. 1 Introduction The very successful concept of graph tree-width was introduced in the context of the Graph Minors project by Robertson and Seymour [RS86,RS91], and it turned out to be very useful for efficiently solving graph problems. Tree-width is a property of undirected graphs. In this paper we will be interested in directed graphs or digraphs. Naturally, a width measure specifically tailored to digraphs with all the nice properties of tree-width would be tremendously useful. The properties of such a measure should include at least the following: i) The width measure is small on many interesting instances. -
Graph Layout for Applications in Compiler Construction
Theoretical Computer Science Theoretical Computer Science 2 I7 ( 1999) 175-2 I4 Graph layout for applications in compiler construction G. Sander * Abstract We address graph visualization from the viewpoint of compiler construction. Most data struc- tures in compilers are large, dense graphs such as annotated control flow graph, syntax trees. dependency graphs. Our main focus is the animation and interactive exploration of these graphs. Fast layout heuristics and powerful browsing methods are needed. We give a survey of layout heuristics for general directed and undirected graphs and present the browsing facilities that help to manage large structured graphs. @ l999-Elsevier Science B.V. All rights reserved Keyrror& Graph layout; Graph drawing; Compiler visualization: Force-directed placement; Hierarchical layout: Compound drawing; Fisheye view 1. Introduction We address graph visualization from the viewpoint of compiler construction. Draw- ings of compiler data structures such as syntax trees, control flow graphs, dependency graphs [63], are used for demonstration, debugging and documentation of compilers. In real-world compiler applications, such drawings cannot be produced manually because the graphs are automatically generated, large, often dense, and seldom planar. Graph layout algorithms help to produce drawings automatically: they calculate positions of nodes and edges of the graph in the plane. Our main focus is the animation and interactive exploration of compiler graphs. Thus. fast layout algorithms are required. Animations show the behaviour of an algorithm by a running sequence of drawings. Thus there is not much time to calculate a layout between two subsequent drawings. In interactive exploration, it is annoying if the user has to wait a long time for a layout. -
Fixed-Parameter Algorithms for Longest Heapable Subsequence and Maximum Binary Tree
Fixed-Parameter Algorithms for Longest Heapable Subsequence and Maximum Binary Tree Karthekeyan Chandrasekaran∗ Elena Grigorescuy Gabriel Istratez Shubhang Kulkarniy Young-San Liny Minshen Zhuy November 23, 2020 Abstract A heapable sequence is a sequence of numbers that can be arranged in a min-heap data structure. Finding a longest heapable subsequence of a given sequence was proposed by Byers, Heeringa, Mitzenmacher, and Zervas (ANALCO 2011) as a generalization of the well-studied longest increasing subsequence problem and its complexity still remains open. An equivalent formulation of the longest heapable subsequence problem is that of finding a maximum-sized binary tree in a given permutation directed acyclic graph (permutation DAG). In this work, we study parameterized algorithms for both longest heapable subsequence as well as maximum-sized binary tree. We show the following results: 1. The longest heapable subsequence problem can be solved in kO(log k)n time, where k is the number of distinct values in the input sequence. 2. We introduce the alphabet size as a new parameter in the study of computational prob- lems in permutation DAGs. Our result on longest heapable subsequence implies that the maximum-sized binary tree problem in a given permutation DAG is fixed-parameter tractable when parameterized by the alphabet size. 3. We show that the alphabet size with respect to a fixed topological ordering can be com- puted in polynomial time, admits a min-max relation, and has a polyhedral description. 4. We design a fixed-parameter algorithm with run-time wO(w)n for the maximum-sized bi- nary tree problem in undirected graphs when parameterized by treewidth w.