An Overview of Graph Covering and Partitioning
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Rounding Algorithms for Covering Problems
Mathematical Programming 80 (1998) 63 89 Rounding algorithms for covering problems Dimitris Bertsimas a,,,1, Rakesh Vohra b,2 a Massachusetts Institute of Technology, Sloan School of Management, 50 Memorial Drive, Cambridge, MA 02142-1347, USA b Department of Management Science, Ohio State University, Ohio, USA Received 1 February 1994; received in revised form 1 January 1996 Abstract In the last 25 years approximation algorithms for discrete optimization problems have been in the center of research in the fields of mathematical programming and computer science. Re- cent results from computer science have identified barriers to the degree of approximability of discrete optimization problems unless P -- NP. As a result, as far as negative results are con- cerned a unifying picture is emerging. On the other hand, as far as particular approximation algorithms for different problems are concerned, the picture is not very clear. Different algo- rithms work for different problems and the insights gained from a successful analysis of a par- ticular problem rarely transfer to another. Our goal in this paper is to present a framework for the approximation of a class of integer programming problems (covering problems) through generic heuristics all based on rounding (deterministic using primal and dual information or randomized but with nonlinear rounding functions) of the optimal solution of a linear programming (LP) relaxation. We apply these generic heuristics to obtain in a systematic way many known as well as new results for the set covering, facility location, general covering, network design and cut covering problems. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V. -
Structural Graph Theory Meets Algorithms: Covering And
Structural Graph Theory Meets Algorithms: Covering and Connectivity Problems in Graphs Saeed Akhoondian Amiri Fakult¨atIV { Elektrotechnik und Informatik der Technischen Universit¨atBerlin zur Erlangung des akademischen Grades Doktor der Naturwissenschaften Dr. rer. nat. genehmigte Dissertation Promotionsausschuss: Vorsitzender: Prof. Dr. Rolf Niedermeier Gutachter: Prof. Dr. Stephan Kreutzer Gutachter: Prof. Dr. Marcin Pilipczuk Gutachter: Prof. Dr. Dimitrios Thilikos Tag der wissenschaftlichen Aussprache: 13. October 2017 Berlin 2017 2 This thesis is dedicated to my family, especially to my beautiful wife Atefe and my lovely son Shervin. 3 Contents Abstract iii Acknowledgementsv I. Introduction and Preliminaries1 1. Introduction2 1.0.1. General Techniques and Models......................3 1.1. Covering Problems.................................6 1.1.1. Covering Problems in Distributed Models: Case of Dominating Sets.6 1.1.2. Covering Problems in Directed Graphs: Finding Similar Patterns, the Case of Erd}os-P´osaproperty.......................9 1.2. Routing Problems in Directed Graphs...................... 11 1.2.1. Routing Problems............................. 11 1.2.2. Rerouting Problems............................ 12 1.3. Structure of the Thesis and Declaration of Authorship............. 14 2. Preliminaries and Notations 16 2.1. Basic Notations and Defnitions.......................... 16 2.1.1. Sets..................................... 16 2.1.2. Graphs................................... 16 2.2. Complexity Classes................................ -
3.1 Matchings and Factors: Matchings and Covers
1 3.1 Matchings and Factors: Matchings and Covers This copyrighted material is taken from Introduction to Graph Theory, 2nd Ed., by Doug West; and is not for further distribution beyond this course. These slides will be stored in a limited-access location on an IIT server and are not for distribution or use beyond Math 454/553. 2 Matchings 3.1.1 Definition A matching in a graph G is a set of non-loop edges with no shared endpoints. The vertices incident to the edges of a matching M are saturated by M (M-saturated); the others are unsaturated (M-unsaturated). A perfect matching in a graph is a matching that saturates every vertex. perfect matching M-unsaturated M-saturated M Contains copyrighted material from Introduction to Graph Theory by Doug West, 2nd Ed. Not for distribution beyond IIT’s Math 454/553. 3 Perfect Matchings in Complete Bipartite Graphs a 1 The perfect matchings in a complete b 2 X,Y-bigraph with |X|=|Y| exactly c 3 correspond to the bijections d 4 f: X -> Y e 5 Therefore Kn,n has n! perfect f 6 matchings. g 7 Kn,n The complete graph Kn has a perfect matching iff… Contains copyrighted material from Introduction to Graph Theory by Doug West, 2nd Ed. Not for distribution beyond IIT’s Math 454/553. 4 Perfect Matchings in Complete Graphs The complete graph Kn has a perfect matching iff n is even. So instead of Kn consider K2n. We count the perfect matchings in K2n by: (1) Selecting a vertex v (e.g., with the highest label) one choice u v (2) Selecting a vertex u to match to v K2n-2 2n-1 choices (3) Selecting a perfect matching on the rest of the vertices. -
Regular Clique Covers of Graphs
Regular clique covers of graphs Dan Archdeacon Dept. of Math. and Stat. University of Vermont Burlington, VT 05405 USA [email protected] Dalibor Fronˇcek Dept. of Math. and Stat. Univ. of Minnesota Duluth Duluth, MN 55812-3000 USA and Technical Univ. Ostrava 70833Ostrava,CzechRepublic [email protected] Robert Jajcay Department of Mathematics Indiana State University Terre Haute, IN 47809 USA [email protected] Zdenˇek Ryj´aˇcek Department of Mathematics University of West Bohemia 306 14 Plzeˇn, Czech Republic [email protected] Jozef Sir´ˇ aˇn Department of Mathematics SvF Slovak Univ. of Technology 81368Bratislava,Slovakia [email protected] Australasian Journal of Combinatorics 27(2003), pp.307–316 Abstract A family of cliques in a graph G is said to be p-regular if any two cliques in the family intersect in exactly p vertices. A graph G is said to have a p-regular k-clique cover if there is a p-regular family H of k-cliques of G such that each edge of G belongs to a clique in H. Such a p-regular k- clique cover is separable if the complete subgraphs of order p that arise as intersections of pairs of distinct cliques of H are mutually vertex-disjoint. For any given integers p, k, ; p<k, we present bounds on the smallest order of a graph that has a p-regular k-clique cover with exactly cliques, and we describe all graphs that have p-regular separable k-clique covers with cliques. 1 Introduction An orthogonal double cover of a complete graph Kn by a graph H is a collection H of spanning subgraphs of Kn, all isomorphic to H, such that each edge of Kn is contained in exactly two subgraphs in H and any two distinct subgraphs in H share exactly one edge. -
Approximating the Minimum Clique Cover and Other Hard Problems in Subtree filament Graphs
Approximating the minimum clique cover and other hard problems in subtree filament graphs J. Mark Keil∗ Lorna Stewart† March 20, 2006 Abstract Subtree filament graphs are the intersection graphs of subtree filaments in a tree. This class of graphs contains subtree overlap graphs, interval filament graphs, chordal graphs, circle graphs, circular-arc graphs, cocomparability graphs, and polygon-circle graphs. In this paper we show that, for circle graphs, the clique cover problem is NP-complete and the h-clique cover problem for fixed h is solvable in polynomial time. We then present a general scheme for developing approximation algorithms for subtree filament graphs, and give approximation algorithms developed from the scheme for the following problems which are NP-complete on circle graphs and therefore on subtree filament graphs: clique cover, vertex colouring, maximum k-colourable subgraph, and maximum h-coverable subgraph. Key Words: subtree filament graph, circle graph, clique cover, NP-complete, approximation algorithm. 1 Introduction Subtree filament graphs were defined in [10] to be the intersection graphs of subtree filaments in a tree, as follows. Consider a tree T = (VT ,ET ) and a multiset of n ≥ 1 subtrees {Ti | 1 ≤ i ≤ n} of T . Let T be embedded in a plane P , and consider the surface S that is perpendicular to P , such that the intersection of S with P is T . A subtree filament corresponding to subtree Ti of T is a connected curve in S, above P , connecting all the leaves of Ti, such that, for all 1 ≤ i ≤ n: • if Ti ∩ Tj = ∅ then the filaments corresponding to Ti and Tj do not intersect, and ∗Department of Computer Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada, S7N 5C9, [email protected], 306-966-4894. -
Edge Clique Covers in Graphs with Independence Number
Edge clique covers in graphs with independence number two Pierre Charbit, Geňa Hahn, Marcin Kamiński, Manuel Lafond, Nicolas Lichiardopol, Reza Naserasr, Ben Seamone, Rezvan Sherkati To cite this version: Pierre Charbit, Geňa Hahn, Marcin Kamiński, Manuel Lafond, Nicolas Lichiardopol, et al.. Edge clique covers in graphs with independence number two. Journal of Graph Theory, Wiley, In press. hal-02969899 HAL Id: hal-02969899 https://hal.archives-ouvertes.fr/hal-02969899 Submitted on 17 Oct 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. ORIG I NAL AR TI CLE Edge CLIQUE COVERS IN GRAPHS WITH INDEPENDENCE NUMBER TWO Pierre Charbit1 | GeNAˇ Hahn 2 | Marcin Kamiński3 | Manuel Lafond4 | Nicolas Lichiardopol5 | Reza NaserASR1 | Ben Seamone2,6 | Rezvan Sherkati7 1Université DE Paris, IRIF, CNRS, F-75013 Paris, FRANCE The EDGE CLIQUE COVER NUMBER ECC¹Gº OF A GRAPH G IS SIZE OF 2Département d’informatique ET DE THE SMALLEST COLLECTION OF COMPLETE SUBGRAPHS WHOSE UNION RECHERCHE opérationnelle, Université DE Montréal, Canada COVERS ALL EDGES OF G. Chen, Jacobson, Kézdy, Lehel, Schein- 3Institute OF Computer Science, UnivERSITY erman, AND WANG CONJECTURED IN 2000 THAT IF G IS CLAw-free, OF WARSAW, POLAND THEN ECC¹Gº IS BOUNDED ABOVE BY ITS ORDER (DENOTED n). -
Bin Completion Algorithms for Multicontainer Packing, Knapsack, and Covering Problems
Journal of Artificial Intelligence Research 28 (2007) 393-429 Submitted 6/06; published 3/07 Bin Completion Algorithms for Multicontainer Packing, Knapsack, and Covering Problems Alex S. Fukunaga [email protected] Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive Pasadena, CA 91108 USA Richard E. Korf [email protected] Computer Science Department University of California, Los Angeles Los Angeles, CA 90095 Abstract Many combinatorial optimization problems such as the bin packing and multiple knap- sack problems involve assigning a set of discrete objects to multiple containers. These prob- lems can be used to model task and resource allocation problems in multi-agent systems and distributed systms, and can also be found as subproblems of scheduling problems. We propose bin completion, a branch-and-bound strategy for one-dimensional, multicontainer packing problems. Bin completion combines a bin-oriented search space with a powerful dominance criterion that enables us to prune much of the space. The performance of the basic bin completion framework can be enhanced by using a number of extensions, in- cluding nogood-based pruning techniques that allow further exploitation of the dominance criterion. Bin completion is applied to four problems: multiple knapsack, bin covering, min-cost covering, and bin packing. We show that our bin completion algorithms yield new, state-of-the-art results for the multiple knapsack, bin covering, and min-cost cov- ering problems, outperforming previous algorithms by several orders of magnitude with respect to runtime on some classes of hard, random problem instances. For the bin pack- ing problem, we demonstrate significant improvements compared to most previous results, but show that bin completion is not competitive with current state-of-the-art cutting-stock based approaches. -
Solving Packing Problems with Few Small Items Using Rainbow Matchings
Solving Packing Problems with Few Small Items Using Rainbow Matchings Max Bannach Institute for Theoretical Computer Science, Universität zu Lübeck, Lübeck, Germany [email protected] Sebastian Berndt Institute for IT Security, Universität zu Lübeck, Lübeck, Germany [email protected] Marten Maack Department of Computer Science, Universität Kiel, Kiel, Germany [email protected] Matthias Mnich Institut für Algorithmen und Komplexität, TU Hamburg, Hamburg, Germany [email protected] Alexandra Lassota Department of Computer Science, Universität Kiel, Kiel, Germany [email protected] Malin Rau Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LIG, 38000 Grenoble, France [email protected] Malte Skambath Department of Computer Science, Universität Kiel, Kiel, Germany [email protected] Abstract An important area of combinatorial optimization is the study of packing and covering problems, such as Bin Packing, Multiple Knapsack, and Bin Covering. Those problems have been studied extensively from the viewpoint of approximation algorithms, but their parameterized complexity has only been investigated barely. For problem instances containing no “small” items, classical matching algorithms yield optimal solutions in polynomial time. In this paper we approach them by their distance from triviality, measuring the problem complexity by the number k of small items. Our main results are fixed-parameter algorithms for vector versions of Bin Packing, Multiple Knapsack, and Bin Covering parameterized by k. The algorithms are randomized with one-sided error and run in time 4k · k! · nO(1). To achieve this, we introduce a colored matching problem to which we reduce all these packing problems. The colored matching problem is natural in itself and we expect it to be useful for other applications. -
A Constructive Formalization of the Weak Perfect Graph Theorem
A Constructive Formalization of the Weak Perfect Graph Theorem Abhishek Kr Singh1 and Raja Natarajan2 1 Tata Institute of Fundamental Research, Mumbai, India [email protected] 2 Tata Institute of Fundamental Research, Mumbai, India [email protected] Abstract The Perfect Graph Theorems are important results in graph theory describing the relationship between clique number ω(G) and chromatic number χ(G) of a graph G. A graph G is called perfect if χ(H) = ω(H) for every induced subgraph H of G. The Strong Perfect Graph Theorem (SPGT) states that a graph is perfect if and only if it does not contain an odd hole (or an odd anti-hole) as its induced subgraph. The Weak Perfect Graph Theorem (WPGT) states that a graph is perfect if and only if its complement is perfect. In this paper, we present a formal framework for working with finite simple graphs. We model finite simple graphs in the Coq Proof Assistant by representing its vertices as a finite set over a countably infinite domain. We argue that this approach provides a formal framework in which it is convenient to work with different types of graph constructions (or expansions) involved in the proof of the Lovász Replication Lemma (LRL), which is also the key result used in the proof of Weak Perfect Graph Theorem. Finally, we use this setting to develop a constructive formalization of the Weak Perfect Graph Theorem. Digital Object Identifier 10.4230/LIPIcs.CPP.2020. 1 Introduction The chromatic number χ(G) of a graph G is the minimum number of colours needed to colour the vertices of G so that no two adjacent vertices get the same colour. -
On Variants of Clique Problems and Their Applications by Zhuoli Xiao B
On Variants of Clique Problems and their Applications by Zhuoli Xiao B.Sc., University of University of Victoria, 2014 A Project Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in the Department of Computer Science c Zhuoli Xiao, 2018 University of Victoria All rights reserved. This project may not be reproduced in whole or in part, by photocopying or other means, without the permission of the author. ii On Variants of Clique Problems and their Applications by Zhuoli Xiao B.Sc., University of University of Victoria, 2014 Supervisory Committee Dr. Ulrike Stege, Supervisor (Department of Computer Science) Dr. Hausi A. Muller, Commitee Member (Department of Computer Science) iii Supervisory Committee Dr. Ulrike Stege, Supervisor (Department of Computer Science) Dr. Hausi A. Muller, Commitee Member (Department of Computer Science) ABSTRACT Clique-based problems, often called cluster problems, receive more and more attention in computer science as well as many of its application areas. Clique-based problems can be used to model a number of real-world problems and with this comes the mo- tivation to provide algorithmic solutions for them. While one can find quite a lot of literature on clique-based problems in general, only for few specific versions exact algorithmic solutions are discussed in detail. In this project, we survey such clique- based problems from the literature, investigate their properties, their exact algorithms and respective running times, and discuss some of their applications. In particular, in depth we consider the two NP-complete clique-based problems Edge Clique Partition and Edge Clique Cover. -
Approximation Algorithm for Vertex Cover with Multiple Covering Constraints
Approximation Algorithm for Vertex Cover with Multiple Covering Constraints Eunpyeong Hong Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan [email protected] Mong-Jen Kao Department of Computer Science and Information Engineering, National Chung-Cheng University, Chiayi, Taiwan [email protected] Abstract We consider the vertex cover problem with multiple coverage constraints in hypergraphs. In this problem, we are given a hypergraph G = (V, E) with a maximum edge size f, a cost function + w : V → Z , and edge subsets P1,P2,...,Pr of E along with covering requirements k1, k2, . , kr for each subset. The objective is to find a minimum cost subset S of V such that, for each edge subset Pi, at least ki edges of it are covered by S. This problem is a basic yet general form of classical vertex cover problem and a generalization of the edge-partitioned vertex cover problem considered by Bera et al. We present a primal-dual algorithm yielding an (f · Hr + Hr)-approximation for this problem, th where Hr is the r harmonic number. This improves over the previous ratio of (3cf log r), where c is a large constant used to ensure a low failure probability for Monte-Carlo randomized algorithms. Compared to previous result, our algorithm is deterministic and pure combinatorial, meaning that no Ellipsoid solver is required for this basic problem. Our result can be seen as a novel reinterpretation of a few classical tight results using the language of LP primal-duality. 2012 ACM Subject Classification Mathematics of computing → Approximation algorithms Keywords and phrases Vertex cover, multiple cover constraints, Approximation algorithm Digital Object Identifier 10.4230/LIPIcs.ISAAC.2018.43 Funding This work is supported in part by Ministry of Science and Technology (MOST), Taiwan, under Grants MOST107-2218-E-194-015-MY3 and MOST106-2221-E-001-006-MY3. -
On the Triangle Clique Cover and $ K T $ Clique Cover Problems
On the Triangle Clique Cover and Kt Clique Cover Problems Hoang Dau Olgica Milenkovic Gregory J. Puleo Abstract An edge clique cover of a graph is a set of cliques that covers all edges of the graph. We generalize this concept to Kt clique cover, i.e. a set of cliques that covers all complete subgraphs on t vertices of the graph, for every t ≥ 1. In particular, we extend a classical result of Erd¨os,Goodman, and P´osa(1966) on the edge clique cover number (t = 2), also known as the intersection number, to the case t = 3. The upper bound is tight, with equality holding only for the Tur´angraph T (n; 3). As part of the proof, we obtain new upper bounds on the classical intersection number, which may be of independent interest. We also extend an algorithm of Scheinerman and Trenk (1999) to solve a weighted version of the Kt clique cover problem on a superclass of chordal graphs. We also prove that the Kt clique cover problem is NP-hard. 1 Introduction A clique in a graph G is a set of vertices that induces a complete subgraph; all graphs considered in this paper are simple and undirected. A vertex clique cover of a graph G is a set of cliques in G that collectively cover all of its vertices. The vertex clique cover number of G, denoted θv(G), is the minimum number of cliques in a vertex clique cover of G. An edge clique cover of a graph G is a set of cliques of G that collectively cover all of its edges.