Approximability of the upper chromatic number of hypergraphs

A C-coloring of a hypergraph H = (X, E) is a vertex coloring φ : X → N such that each edge E ∈ E has at least two vertices with a common color. The related parameter over(χ, -) (H), called the upper chromatic number of H, is the maximum number of colors in a C-coloring of H. A hypertree is a hypergraph which has a host tree T such that each edge E ∈ E induces a connected subgraph in T. Notations n and m stand for the number of vertices and edges, respectively, in a generic input hypergraph. We establish guaranteed polynomial-time approximation ratios for the difference n - over(χ, -) (H), which is 2 + 2 ln (2 m) on hypergraphs in general, and 1 + ln m on hypertrees. The latter ratio is essentially tight as we show that n - over(χ, -) (H) cannot be approximated within (1 - ε{lunate}) ln m on hypertrees (unless NP⊆ DTIME(nO (log log n)) ). Furthermore, over(χ, -) (H) does not have O (n1 - ε{lunate})-approximation and cannot be approximated within additive error o (n) on the class of hypertrees (unless P = NP). © 2014 Elsevier B.V. All rights reserved

Maximum number of colors in hypertrees of bounded degree

The upper chromatic number (Formula presented.) of a hypergraph (Formula presented.) is the maximum number of colors that can occur in a vertex coloring (Formula presented.) such that no edge (Formula presented.) is completely multicolored. A hypertree (also called arboreal hypergraph) is a hypergraph whose edges induce subtrees on a fixed tree graph. It has been shown that on hypertrees it is algorithmically hard not only to determine exactly but also to approximate the value of (Formula presented.), unless (Formula presented.). In sharp contrast to this, here we prove that if the input is restricted to hypertrees (Formula presented.) of bounded maximum vertex degree, then (Formula presented.) can be determined in linear time if an underlying tree is also given in the input. Consequently, (Formula presented.) on hypertrees is fixed parameter tractable in terms of maximum degree. © 2014 Springer-Verlag Berlin Heidelberg

Műszaki informatikai problémákhoz kapcsolódó diszkrét matematikai modellek vizsgálata = Discrete mathematical models related to problems in informatics

Diszkrét matematikai módszerekkel strukturális és kvantitatív összefüggéseket bizonyítottunk; algoritmusokat terveztünk, komplexitásukat elemeztük. Az eredmények a gráfok és hipergráfok elméletéhez, valamint on-line ütemezéshez kapcsolódnak. Néhány kiemelés: - Pontosan leírtuk azokat a szerkezeti feltételeket, amelyeknek teljesülni kell ahhoz, hogy egy kommunikációs hálózatban és annak minden összefüggő részében legyen olyan, megadott típusú összefüggő részhálózat, ahonnan az összes többi elem közvetlenül elérhető. (A probléma két évtizeden át megoldatlan volt.) - Aszimptotikusan pontos becslést adtunk egy n-elemű alaphalmaz olyan, k-asokból álló halmazrendszereinek minimális méretére, amelyekben minden k-osztályú partícióhoz van olyan halmaz, ami az összes partíció-osztályt metszi. (Nyitott probléma volt 1973 óta, több szerző egymástól függetlenül is felvetette.) - Halmazrendszerek partícióira az eddigieknél általánosabb modellt vezettünk be, megvizsgáltuk részosztályainak hierarchikus szerkezetét és hatékony algoritmusokat adtunk. (Sok alkalmazás várható az erőforrás-allokáció területén.) - Kidolgoztunk egy módszert, amellyel lokálisan véges pozíciós játékok nyerő stratégiája megtalálható mindössze lineáris méretű memória használatával. - Félig on-line ütemezési algoritmusokat terveztünk (kétgépes feladatra, nem azonos sebességű processzorokra), amelyeknek versenyképességi aránya bizonyítottan jobb, mint ami a legjobb teljesen on-line módszerekkel elérhető. | Applying discrete mathematical methods, we proved structural and quantitative relations, designed algorithms and analyzed their complexity. The results deal with graph and hypergraph theory and on-line scheduling. Some selected ones are: - We described the exact structural conditions which have to hold in order that an intercommunication network and each of its connected parts contain a connected subnetwork of prescribed type, from which all the other nodes of the network can be reached via direct link. (This problem was open for two decades.) - We gave asymptotically tight estimates on the minimum size of set systems of k-element sets over an n-element set such that, for each k-partition of the set, the set system contains a k-set meeting all classes of the partition. (This was an open problem since 1973, raised by several authors independently.) - We introduced a new model, more general than the previous ones, for partitions of set systems. We studied the hierarchic structure of its subclasses, and designed efficient algorithms. (Many applications are expected in the area of resource allocation.) - We developed a method to learn winning strategies in locally finite positional games, which requires linear-size memory only. - We designed semi-online scheduling algorithms (for two uniform processors of unequal speed), whose competitive ratio provably beats the best possible one achievable in the purely on-line setting

About perfection of circular mixed hypergraphs

A mixed hypergraph is a triple H = (X,C,D), where X is the vertex set and each of C and D is a family of subsets of X, the C-edges and D-edges, respectively. A proper k-coloring of H is a mapping c : X → {1,...,k} such that each C-edge has two vertices with a common color and each D-edge has two vertices with different colors. Maximum number of colors in a coloring using all the colors is called upper chromatic number χ ̄(H). Maximum cardinality of subset of vertices which contains no C-edge is C-stability number αC (H). A mixed hypergraph is called C-perfect if χ ̄ (H') = αC (H') for any induced subhypergraph H'. A mixed hyper- graph H is called circular if there exists a host cycle on the vertex set X such that every edge (C- or D-) induces a connected subgraph on the host cycle. We give a characterization of C-perfect circular mixed hypergraphs

Chromatic polynomials of some sunflower mixed hypergraphs

The theory of mixed hypergraphs coloring has been first introduced by Voloshin in 1993 and it has been growing ever since. The proper coloring of a mixed hypergraph H = (X; C;D) is the coloring of the vertex set X so that no D-hyperedge is monochromatic and no C-hyperedge is polychromatic. A mixed hypergraph with hyperedges of type D, C or B is commonly known as a D-, C-, or B-hypergraph respectively, where B = C = D. D-hypergraph colorings are the classic hypergraph colorings which have been widely studied. The chromatic polynomial P(H;λ) of a mixed hypergraph H is the function that counts the number of proper λ-colorings, which are mappings. Recently, Walter published [15] some results concerning the chromatic polynomial of some non-uniform D-sunflower. In this paper, we present an alternative proof of his result and extend his formula to those of non-uniform C-sunflowers and B-sunflowers. Some results of a new but related member of sunflowers are also presented

Chromatic Polynomials of Some Mixed Hypergraphs

Motivated by a recent result of M. Walter [Electron. J. Comb. 16, No. 1, Research Paper R94, 16 p. (2009; Zbl 1186.05059)] concerning the chromatic polynomials of some hypergraphs, we present the chromatic polynomials of several (non-uniform) mixed hypergraphs. We use a recursive process for generating explicit formulae for linear mixed hypercacti and multi-bridge mixed hypergraphs using a decomposition of the underlying hypergraph into blocks, defined via chains. Further, using an algebra software package such as Maple, one can use the basic formulae and process demonstrated in this paper to generate the chromatic polynomials for any linear mixed hypercycle, unicyclic mixed hypercyle, mixed hypercactus and multi-bridge mixed hypergraph. We also give the chromatic polynomials of several examples in illustration of the process including the formulae for some mixed sunflowers