arXiv subjects

Arash Rafiey

Publications and source records attributed to Arash Rafiey.

At least 19 recordsLinked to original sources

arXiv2026

Odd Cycle Transversal in $P_k$-Free Graphs

The Odd Cycle Transversal (OCT) problem, which asks for a minimum subset of vertices whose removal renders a graph bipartite, is a central problem in algorithmic graph theory. It is known to be NP-complete even on $P_k$-free graphs for $k \ge 6$. Furthermore, assuming the Unique Games Conjecture (UGC), OCT does not admit a constant-factor approximation algorithm on general graphs. Motivated by these hardness results, we investigate the approximability of OCT on $P_k$-free graphs. We first establish that the problem becomes polynomial-time solvable on specific subclasses of $P_k$-free graphs, most notably $(P_6, C_3)$-free graphs, by exploiting a structural decomposition into rings of bipartite graphs. Leveraging these tractable substructures as a basis, we present a constant-factor approximation algorithm for OCT on general $P_k$-free graphs. We achieve an approximation ratio of $k-2$ when $k$ is odd and $k-3$ when $k$ is even. These results provide the first nontrivial constant-factor approximations for this class dependent on $k$, aligning with the UGC implication that no approximation factor independent of $k$ is likely to exist.

cs.DS↗

arXiv2025

Interval H-graphs : Recognition and forbidden obstructions

We introduce the class of interval $H$-graphs, which is the generalization of interval graphs, particularly interval bigraphs. For a fixed graph $H$ with vertices $a_1,a_2,\dots,a_k$, we say that an input graph $G$ with given partition $V_1,\dots,V_k$ of its vertices is an interval $H$-graph if each vertex $v \in G$ can be represented by an interval $I_v$ from a real line so that $u \in V_i$ and $v \in V_j$ are adjacent if and only if $a_ia_j$ is an edge of $H$ and intervals $I_u$ and $I_v$ intersect. $G$ is called interval $k$-graph if $H$ is a complete graph on $k$ vertices. and interval bigraph when $k=2$. We study the ordering characterization and forbidden obstructions of interval $k$-graphs and present a polynomial-time recognition algorithm for them. Additionally, we discuss how this algorithm can be extended to recognize general interval $H$-graphs. Special cases of interval $k$-graphs, particularly comparability interval $k$-graphs, were previously studied in [2], where the complexity interval $k$-graph recognition was posed as an open problem.

cs.DM↗

arXiv2023

Min orderings and list homomorphism dichotomies for signed and unsigned graphs

The CSP dichotomy conjecture has been recently established, but a number of other dichotomy questions remain open, including the dichotomy classification of list homomorphism problems for signed graphs. Signed graphs arise naturally in many contexts, including for instance nowhere-zero flows for graphs embedded in non-orientable surfaces. For a fixed signed graph $\widehat{H}$, the list homomorphism problem asks whether an input signed graph $\widehat{G}$ with lists $L(v) \subseteq V(\widehat{H}), v \in V(\widehat{G}),$ admits a homomorphism $f$ to $\widehat{H}$ with all $f(v) \in L(v), v \in V(\widehat{G})$. Usually, a dichotomy classification is easier to obtain for list homomorphisms than for homomorphisms, but in the context of signed graphs a structural classification of the complexity of list homomorphism problems has not even been conjectured, even though the classification of the complexity of homomorphism problems is known. Kim and Siggers have conjectured a structural classification in the special case of ``weakly balanced" signed graphs. We confirm their conjecture for reflexive and irreflexive signed graphs; this generalizes previous results on weakly balanced signed trees, and weakly balanced separable signed graphs \cite{separable,trees}. In the reflexive case, the result was first presented in \cite{KS}, with the proof using some of our results included in this paper. In fact, here we present our full proof, as an alternative to the proof in \cite{KS}. In particular, we provide direct polynomial algorithms where previously algorithms relied on general dichotomy theorems. The irreflexive results are new, and their proof depends on first deriving a theorem on extensions of min orderings of (unsigned) bipartite graphs, which is interesting on its own. [shortened, full abstract in PDF]

math.CO↗

arXiv2022

Toward a Dichotomy for Approximation of $H$-coloring

Given two (di)graphs G, H and a cost function $c:V(G)\times V(H) \to \mathbb{Q}_{\geq 0}\cup\{+\infty\}$, in the minimum cost homomorphism problem, MinHOM(H), goal is finding a homomorphism $f:V(G)\to V(H)$ (a.k.a H-coloring) that minimizes $\sum\limits_{v\in V(G)}c(v,f(v))$. The complexity of exact minimization of this problem is well understood [34], and the class of digraphs H, for which the MinHOM(H) is polynomial time solvable is a small subset of all digraphs. In this paper, we consider the approximation of MinHOM within a constant factor. For digraphs, MinHOM(H) is not approximable if H contains a digraph asteroidal triple (DAT). We take a major step toward a dichotomy classification of approximable cases. We give a dichotomy classification for approximating the MinHOM(H) when H is a graph. For digraphs, we provide constant factor approximation algorithms for two important classes of digraphs, namely bi-arc digraphs (digraphs with a conservative semi-lattice polymorphism or min-ordering), and k-arc digraphs (digraphs with an extended min-ordering). Specifically, we show that: 1. Dichotomy for Graphs: MinHOM(H) has a $2|V(H)|$-approximation algorithm if graph H admits a conservative majority polymorphims (i.e. H is a bi-arc graph), otherwise, it is inapproximable; 2. MinHOM(H) has a $|V(H)|^2$-approximation algorithm if H is a bi-arc digraph; 3. MinHOM(H) has a $|V(H)|^2$-approximation algorithm if H is a k-arc digraph. In conclusion, we show the importance of these results and provide insights for achieving a dichotomy classification of approximable cases. Our constant factors depend on the size of H. However, the implementation of our algorithms provides a much better approximation ratio. It leaves open to investigate a classification of digraphs H, where MinHOM(H) admits a constant factor approximation algorithm that is independent of H.

cs.DS↗

arXiv2020

Digraph homomorphism problem and weak near unanimity polymorphism

We consider the problem of finding a homomorphism from an input digraph $G$ to a fixed digraph $H$. We show that if $H$ admits a weak near unanimity polymorphism $ϕ$ then deciding whether $G$ admits a homomorphism to $H$ (HOM($H$)) is polynomial-time solvable. This gives proof of the dichotomy conjecture (now dichotomy theorem) by Feder and Vardi. Our approach is combinatorial, and it is simpler than the two algorithms found by Bulatov and Zhuk. We have implemented our algorithm and show some experimental results. We use our algorithm together with the recent result [38] for recognition of Maltsev polymorphisms and decide in polynomial time if a given relational structure $\mathcal{R}$ admits a weak near unanimity polymorphism.

cs.CC↗

arXiv2020

Digraphs Homomorphism Problems with Maltsev Condition

We consider a generalization of finding a homomorphism from an input digraph $G$ to a fixed digraph $H$, HOM($H$). In this setting, we are given an input digraph $G$ together with a list function from $G$ to $2^H$. The goal is to find a homomorphism from $G$ to $H$ with respect to the lists if one exists. We show that if the list function is a Maltsev polymorphism then deciding whether $G$ admits a homomorphism to $H$ is polynomial time solvable. In our approach, we only use the existence of the Maltsev polymorphism. Furthermore, we show that deciding whether a relational structure $\mathcal{R}$ admits a Maltsev polymorphism is a special case of finding a homormphism from a graph $G$ to a graph $H$ and a list function with a Maltsev polymorphism. Since the existence of Maltsev is not required in our algorithm, we can decide in polynomial time whether the relational structure $\mathcal{R}$ admits Maltsev or not. We also discuss forbidden obstructions for the instances admitting Maltsev list polymorphism. We have implemented our algorithm and tested on instances arising from linear equations, and other types of instances.

cs.DS↗

arXiv2020

Dichotomy for Digraph Homomorphism Problems

We consider the problem of finding a homomorphism from an input digraph $G$ to a fixed digraph $H$. We show that if $H$ admits a weak-near-unanimity polymorphism $ϕ$ then deciding whether $G$ admits a homomorphism to $H$ (HOM($H$)) is polynomial time solvable? This gives a proof of the dichotomy conjecture (now dichotomy theorem) by Feder and Vardi [29]. Our approach is combinatorial, and it is simpler than the two algorithms found by Bulatov [9] and Zhuk [46] in 2017. We have implemented our algorithm and show some experimental results.

cs.CC↗

arXiv2020

Bi-Arc Digraphs and Conservative Polymorphisms

In this paper we study the class of bi-arc digraphs, important from two seemingly unrelated perspectives. On the one hand, they are precisely the digraphs that admit certain polymorphisms of interest in the study of constraint satisfaction problems; on the other hand, they are a very broad generalization of interval graphs. Bi-arc digraphs is the class of digraphs that admit conservative semilattice polymorphisms. There is much interest in understanding structures that admit particular types of polymorphisms, and especially in their recognition algorithms. (Such problems are referred to as metaproblems.) Surprisingly, the class of bi-arc digraphs also describes the class of digraphs that admit certain other kinds of conservative polymorphisms. Thus solving the recognition problem for bi-arc digraphs solves the metaproblem for digraphs for several types of conservative polymorphisms. The complexity of the recognition problem for digraphs with conservative semilattice polymorphisms was an open problem, while it was known to be NP-complete for certain more complex relational structures. We complement our result by providing a complete dichotomy classification of which general relational structures have polynomial or NP-complete recognition problems for the existence of conservative semilattice polymorphisms. Bi-arc digraphs also generalizes the class of interval graphs; in fact it reduces to the class of interval graphs for symmetric and reflexive digraphs. It is much broader than interval graphs and includes other generalizations of interval graphs such as co-threshold tolerance graphs and adjusted interval digraphs. Yet, it is still a reasonable extension of interval graphs, in the sense that it keeps much of the appeal of interval graphs. Our main result is a forbidden obstruction characterization of, and a polynomial recognition for, the class of bi-arc digraphs.

cs.DS↗

arXiv2018

Interval-Like Graphs and Digraphs

We unify several seemingly different graph and digraph classes under one umbrella. These classes are all broadly speaking different generalizations of interval graphs, and include, in addition to interval graphs, also adjusted interval digraphs, threshold graphs, complements of threshold tolerance graphs (known as `co-TT' graphs), bipartite interval containment graphs, bipartite co-circular arc graphs, and two-directional orthogonal ray graphs. (The last three classes coincide, but have been investigated in different contexts.) This common view is made possible by introducing loops. We also show that all the above classes are united by a common ordering characterization, the existence of a min ordering. We propose a common generalization of all these graph and digraph classes, namely signed-interval digraphs, and show that they are precisely the digraphs that are characterized by the existence of a min ordering. We also offer an alternative geometric characterization of these digraphs. For most of the above example graph and digraph classes, we show that they are exactly those signed-interval digraphs that satisfy a suitable natural restriction on the digraph, like having all loops, or having a symmetric edge-set, or being bipartite. (For instance co-TT graphs are precisely those signed-interval digraphs that have each edge symmetric.) We also offer some discussion of recognition algorithms and characterizations, saving the details for future papers.

cs.DM↗

arXiv2018

Recognizing Interval Bigraphs by Forbidden Patterns

Let H be a connected bipartite graph with n nodes and m edges. We give an O(nm) time algorithm to decide whether H is an interval bigraph. The best known algorithm has time complexity O(nm^6(m + n) \log n) and it was developed in 1997 [18]. Our approach is based on an ordering characterization of interval bigraphs introduced by Hell and Huang [13]. We transform the problem of finding the desired ordering to choosing strong components of a pair-digraph without creating conflicts. We make use of the structure of the pair-digraph as well as decomposition of bigraph H based on the special components of the pair-digraph. This way we make explicit what the difficult cases are and gain efficiency by isolating such situations.

cs.DS↗

arXiv2016

PTAS for Ordered Instances of Resource Allocation Problems with Restrictions on Inclusions

We consider the problem of allocating a set $I$ of $m$ indivisible resources (items) to a set $P$ of $n$ customers (players) competing for the resources. Each resource $j \in I$ has a same value $v_j > 0$ for a subset of customers interested in $j$, and zero value for the remaining customers. The utility received by each customer is the sum of the values of the resources allocated to her. The goal is to find a feasible allocation of the resources to the interested customers such that for the Max-Min allocation problem (Min-Max allocation problem) the minimum of the utilities (maximum of the utilities) received by the customers is maximized (minimized). The Max-Min allocation problem is also known as the \textit{Fair Allocation problem}, or the \textit{Santa Claus problem}. The Min-Max allocation problem is the problem of Scheduling on Unrelated Parallel Machines, and is also known as the $R \, | \, | C_{\max}$ problem. In this paper, we are interested in instances of the problem that admit a Polynomial Time Approximation Scheme (PTAS). We show that an ordering property on the resources and the customers is important and paves the way for a PTAS. For the Max-Min allocation problem, we start with instances of the problem that can be viewed as a \textit{convex bipartite graph}; a bipartite graph for which there exists an ordering of the resources such that each customer is interested in (has a positive evaluation for) a set of \textit{consecutive} resources. We demonstrate a PTAS for the inclusion-free cases. This class of instances is equivalent to the class of bipartite permutation graphs. For the Min-Max allocation problem, we also obtain a PTAS for inclusion-free instances. These instances are not only of theoretical interest but also have practical applications.

cs.DS↗

arXiv2016

Ordering with precedence constraints and budget minimization

We introduce a variation of the scheduling with precedence constraints problem that has applications to molecular folding and production management. We are given a bipartite graph $H=(B,S)$. Vertices in $B$ are thought of as goods or services that must be \emph{bought} to produce items in $S$ that are to be \emph{sold}. An edge from $j\in S$ to $i\in B$ indicates that the production of $j$ requires the purchase of $i$. Each vertex in $B$ has a cost, and each vertex in $S$ results in some gain. The goal is to obtain an ordering of $B\cup S$ that respects the precedence constraints and maximizes the minimal net profit encountered as the vertices are processed. We call this optimal value the \emph{budget} or \emph{capital} investment required for the bipartite graph, and refer to our problem as \emph{the bipartite graph ordering problem}. The problem is equivalent to a version of an NP-complete molecular folding problem that has been studied recently [12]. Work on the molecular folding problem has focused on heuristic algorithms and exponential-time exact algorithms for the un-weighted problem where costs are $\pm 1$ and when restricted to graphs arising from RNA folding. The bipartite graph present work seeks exact algorithms for solving the bipartite ordering problem. We demonstrate an algorithm that computes the optimal ordering in time $O^*(2^n)$ when $n$ is the number of vertices in the input bipartite graph. Our main result is a general strategy that can be used to find an optimal ordering in polynomial time for bipartite graphs that satisfy certain properties. We apply the technique to a variety of graph classes, obtaining polynomial-time solutions to the bipartite graph ordering problem for bipartite permutation graphs, trivially perfect, co-bipartite graphs, and trees.

cs.DM↗

arXiv2016

Single Exponential FPT Algorithm for Interval Vertex Deletion and Interval Completion Problem

Let G be an input graph with n vertices and m edges and let k be a fixed parameter. We provide a single exponential FPT algorithm with running time O(c^kn(n+m)), c= min {18,k} that turns graph G into an interval graph by deleting at most k vertices from G. This solves an open problem posed by D.Marx [19]. We also provide a single exponential FPT algorithm with running time O(c^kn(n+m)), c= min {17,k} that turns G into an interval graph by adding at most$k edges. The first FPT algorithm with run time O(k^{2k}n^3m) appeared in STOC 2007 [24]. Our algorithm is the the first single exponential FPT algorithm that improves the running time of the previous algorithm. The algorithms are based on a structural decomposition of G into smaller subgraphs when G is free from small interval graph obstructions. The decomposition allows us to manage the search tree more efficiently.

cs.DS↗

arXiv2015

Approximation Algorithms for Generalized MST and TSP in Grid Clusters

We consider a special case of the generalized minimum spanning tree problem (GMST) and the generalized travelling salesman problem (GTSP) where we are given a set of points inside the integer grid (in Euclidean plane) where each grid cell is $1 \times 1$. In the MST version of the problem, the goal is to find a minimum tree that contains exactly one point from each non-empty grid cell (cluster). Similarly, in the TSP version of the problem, the goal is to find a minimum weight cycle containing one point from each non-empty grid cell. We give a $(1+4\sqrt{2}+ε)$ and $(1.5+8\sqrt{2}+ε)$-approximation algorithm for these two problems in the described setting, respectively. Our motivation is based on the problem posed in [7] for a constant approximation algorithm. The authors designed a PTAS for the more special case of the GMST where non-empty cells are connected end dense enough. However, their algorithm heavily relies on this connectivity restriction and is unpractical. Our results develop the topic further.

cs.DM↗

arXiv2014

Pattern overlap implies runaway growth in hierarchical tile systems

We show that in the hierarchical tile assembly model, if there is a producible assembly that overlaps a nontrivial translation of itself consistently (i.e., the pattern of tile types in the overlap region is identical in both translations), then arbitrarily large assemblies are producible. The significance of this result is that tile systems intended to controllably produce finite structures must avoid pattern repetition in their producible assemblies that would lead to such overlap. This answers an open question of Chen and Doty (SODA 2012), who showed that so-called "partial-order" systems producing a unique finite assembly *and" avoiding such overlaps must require time linear in the assembly diameter. An application of our main result is that any system producing a unique finite assembly is automatically guaranteed to avoid such overlaps, simplifying the hypothesis of Chen and Doty's main theorem.

cs.CG↗

arXiv2014

Ordering without forbidden patterns

Let F be a set of ordered patterns, i.e., graphs whose vertices are linearly ordered. An F-free ordering of the vertices of a graph H is a linear ordering of V(H) such that none of patterns in F occurs as an induced ordered subgraph. We denote by ORD(F) the decision problem asking whether an input graph admits an F-free ordering; we also use ORD(F) to denote the class of graphs that do admit an F-free ordering. It was observed by Damaschke (and others) that many natural graph classes can be described as ORD(F) for sets F of small patterns (with three or four vertices). Damaschke also noted that for many sets F consisting of patterns with three vertices, ORD(F) is polynomial-time solvable by known algorithms or their simple modifications. We complete the picture by proving that all these problems can be solved in polynomial time. In fact, we provide a single master algorithm, i.e., we solve in polynomial time the problem $ORD_3$ in which the input is a set F of patterns with at most three vertices and a graph H, and the problem is to decide whether or not H admits an F-free ordering of the vertices. Our algorithm certifies non-membership by a forbidden substructure, and thus provides a single forbidden structure characterization for all the graph classes described by some ORD(F) with F consisting of patterns with at most three vertices. Many of the problems ORD(F) with F consisting of larger patterns have been shown to be NP-complete by Duffus, Ginn, and Rodl, and we add two simple examples. We also discuss a bipartite version of the problem, BORD(F), in which the input is a bipartite graph H with a fixed bipartition of the vertices, and we are given a set F of bipartite patterns. We also describe some examples of digraph ordering problems and algorithms. We conjecture that for every set F of forbidden patterns, ORD(F) is either polynomial or NP-complete.

cs.DM↗

arXiv2014

Interval minors of complete bipartite graphs

Interval minors of bipartite graphs were recently introduced by Jacob Fox in the study of Stanley-Wilf limits. We investigate the maximum number of edges in $K_{r,s}$-interval minor free bipartite graphs. We determine exact values when $r=2$ and describe the extremal graphs. For $r=3$, lower and upper bounds are given and the structure of $K_{3,s}$-interval minor free graphs is studied.

math.CO↗

arXiv2014

Finding minimum Tucker submatrices

A binary matrix has the Consecutive Ones Property (C1P) if its columns can be ordered in such a way that all 1s on each row are consecutive. These matrices are used for DNA physical mapping and ancestral genome reconstruction in computational biology on the other hand they represents a class of convex bipartite graphs and are of interest of algorithm graph theory researchers. Tucker gave a forbidden submartices characterization of matrices that have C1P property in 1972. Booth and Lucker (1976) gave a first linear time recognition algorithm for matrices with C1P property and then in 2002, Habib, et al. gave a simpler linear time recognition algorithm. There has been substantial amount of works on efficiently finding minimum size forbidden submatrix. Our algorithm is at least $n$ times faster than the existing algorithm where $n$ is the number of columns of the input matrix.

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