Deterministically Isolating a Perfect Matching in Bipartite Planar Graphs

We present a deterministic Logspace procedure, which, given a bipartite planar graph on n vertices, assigns O(log n) bits long weights to its edges so that the minimum weight perfect matching in the graph becomes unique. The Isolation Lemma as described in Mulmuley et al. (Combinatorica 7(1):105–131, 1987) achieves the same for general graphs using randomness, whereas we can do it deterministically when restricted to bipartite planar graphs. As a consequence, we reduce both decision and construction versions of the perfect matching problem in bipartite planar graphs to testing whether a matrix is singular, under the promise that its determinant is 0 or 1, thus obtaining a highly parallel SPL\mathsf{SPL} algorithm for both decision and construction versions of the bipartite perfect matching problem. This improves the earlier known bounds of non-uniform SPL\mathsf{SPL} by Allender et al. (J. Comput. Syst. Sci. 59(2):164–181, 1999) and NC\mathsf{NC} ² by Miller and Naor (SIAM J. Comput. 24:1002–1017, 1995), and by Mahajan and Varadarajan (Proceedings of the Thirty-Second Annual ACM Symposium on Theory of Computing (STOC), pp. 351–357, 2000). It also rekindles the hope of obtaining a deterministic parallel algorithm for constructing a perfect matching in non-bipartite planar graphs, which has been open for a long time. Further we try to find the lower bound on the number of bits needed for deterministically isolating a perfect matching. We show that our particular method for isolation will require Ω(log n) bits. Our techniques are elementary.     

Approximating Minimum-Power Degree and Connectivity Problems

Power optimization is a central issue in wireless network design. Given a graph with costs on the edges, the power of a node is the maximum cost of an edge incident to it, and the power of a graph is the sum of the powers of its nodes. Motivated by applications in wireless networks, we consider several fundamental undirected network design problems under the power minimization criteria. Given a graph G=(V,E)\mathcal{G}=(V,\mathcal{E}) with edge costs {c(e):e∈ℰ} and degree requirements {r(v):v∈V}, the Minimum-Power Edge-Multi-Cover\textsf{Minimum-Power Edge-Multi-Cover} (MPEMC\textsf{MPEMC} ) problem is to find a minimum-power subgraph G of G\mathcal{G} so that the degree of every node v in G is at least r(v). We give an O(log n)-approximation algorithms for MPEMC\textsf{MPEMC} , improving the previous ratio O(log ⁴ n). This is used to derive an O(log n+α)-approximation algorithm for the undirected $\textsf{Minimum-Power $\textsf{Minimum-Power ($\textsf{MP$\textsf{MP ) problem, where α is the best known ratio for the min-cost variant of the problem. Currently, _boxclosen-k)\alpha=O(\log k\cdot \log\frac{n}{n-k}) which is O(log k) unless k=n−o(n), and is O(log ² k)=O(log ² n) for k=n−o(n). Our result shows that the min-power and the min-cost versions of the $\textsf{$\textsf{ problem are equivalent with respect to approximation, unless the min-cost variant admits an o(log n)-approximation, which seems to be out of reach at the moment.     

The 1-Versus-2 Queries Problem Revisited

The 1-versus-2 queries problem, which has been extensively studied in computational complexity theory, asks in its generality whether every efficient algorithm that makes at most 2 queries to a Σ _k ^p -complete language L _k has an efficient simulation that makes at most 1 query to L _k . We obtain solutions to this problem for hypotheses weaker than previously considered. We prove that:

The 1-Fixed-Endpoint Path Cover Problem is Polynomial on Interval Graphs

We consider a variant of the path cover problem, namely, the k-fixed-endpoint path cover problem, or kPC for short, on interval graphs. Given a graph G and a subset T\mathcal{T} of k vertices of V(G), a k-fixed-endpoint path cover of G with respect to T\mathcal{T} is a set of vertex-disjoint paths ℘ that covers the vertices of G such that the k vertices of T\mathcal{T} are all endpoints of the paths in ℘. The kPC problem is to find a k-fixed-endpoint path cover of G of minimum cardinality; note that, if T\mathcal{T} is empty the stated problem coincides with the classical path cover problem. In this paper, we study the 1-fixed-endpoint path cover problem on interval graphs, or 1PC for short, generalizing the 1HP problem which has been proved to be NP-complete even for small classes of graphs. Motivated by a work of Damaschke (Discrete Math. 112:49–64, 1993), where he left both 1HP and 2HP problems open for the class of interval graphs, we show that the 1PC problem can be solved in polynomial time on the class of interval graphs. We propose a polynomial-time algorithm for the problem, which also enables us to solve the 1HP problem on interval graphs within the same time and space complexity.     

The Directed Orienteering Problem

This paper studies vehicle routing problems on asymmetric metrics. Our starting point is the directed k-TSP problem: given an asymmetric metric (V,d), a root r∈V and a target k≤|V|, compute the minimum length tour that contains r and at least k other vertices. We present a polynomial time O(\fraclog² nloglogn·logk)O(\frac{\log^{2} n}{\log\log n}\cdot\log k)-approximation algorithm for this problem. We use this algorithm for directed k-TSP to obtain an O(\fraclog² nloglogn)O(\frac{\log^{2} n}{\log\log n})-approximation algorithm for the directed orienteering problem. This answers positively, the question of poly-logarithmic approximability of directed orienteering, an open problem from Blum et al. (SIAM J. Comput. 37(2):653–670, 2007). The previously best known results were quasi-polynomial time algorithms with approximation guarantees of O(log ² k) for directed k-TSP, and O(log n) for directed orienteering (Chekuri and Pal in IEEE Symposium on Foundations in Computer Science, pp. 245–253, 2005). Using the algorithm for directed orienteering within the framework of Blum et al. (SIAM J. Comput. 37(2):653–670, 2007) and Bansal et al. (ACM Symposium on Theory of Computing, pp. 166–174, 2004), we also obtain poly-logarithmic approximation algorithms for the directed versions of discounted-reward TSP and vehicle routing problem with time-windows.     

Fast Evaluation of Interlace Polynomials on Graphs of Bounded Treewidth

We consider the multivariate interlace polynomial introduced by Courcelle (Electron. J. Comb. 15(1), 2008), which generalizes several interlace polynomials defined by Arratia, Bollobás, and Sorkin (J. Comb. Theory Ser. B 92(2):199–233, 2004) and by Aigner and van der Holst (Linear Algebra Appl., 2004). We present an algorithm to evaluate the multivariate interlace polynomial of a graph with n vertices given a tree decomposition of the graph of width k. The best previously known result (Courcelle, Electron. J. Comb. 15(1), 2008) employs a general logical framework and leads to an algorithm with running time f(k)⋅n, where f(k) is doubly exponential in k. Analyzing the GF(2)-rank of adjacency matrices in the context of tree decompositions, we give a faster and more direct algorithm. Our algorithm uses 2^3k2+O(k)·n2^{3k^{2}+O(k)}\cdot n arithmetic operations and can be efficiently implemented in parallel.     

Minimum Augmentation of Edge-Connectivity between Vertices and Sets of Vertices in Undirected Graphs

Given an undirected multigraph G=(V,E), a family $\mathcal{W}Given an undirected multigraph G=(V,E), a family W\mathcal{W} of areas W⊆V, and a target connectivity k≥1, we consider the problem of augmenting G by the smallest number of new edges so that the resulting graph has at least k edge-disjoint paths between v and W for every pair of a vertex v∈V and an area W ? WW\in \mathcal{W} . So far this problem was shown to be NP-complete in the case of k=1 and polynomially solvable in the case of k=2. In this paper, we show that the problem for k≥3 can be solved in O(m+n(k ³+n ²)(p+kn+nlog n)log k+pkn ³log (n/k)) time, where n=|V|, m=|{{u,v}|(u,v)∈E}|, and p=|W|p=|\mathcal{W}| .     

Indexing Factors with Gaps

Indexing of factors or substrings is a widely used and useful technique in stringology and can be seen as a tool in solving diverse text algorithmic problems. A gapped-factor is a concatenation of a factor of length k, a gap of length d and another factor of length k′. Such a gapped factor is called a (k−d−k′)-gapped-factor. The problem of indexing the gapped-factors was considered recently by Peterlongo et al. (In: Stringology, pp. 182–196, 2006). In particular, Peterlongo et al. devised a data structure, namely a gapped factor tree (GFT) to index the gapped-factors. Given a text of length n over the alphabet Σ and the values of the parameters k, d and k′, the construction of GFT requires O(n|Σ|) time. Once GFT is constructed, a given (k−d−k′)-gapped-factor can be reported in O(k+k′+Occ) time, where Occ is the number of occurrences of that factor in  . In this paper, we present a new improved indexing scheme for the gapped-factors. The improvements we achieve come from two aspects. Firstly, we generalize the indexing data structure in the sense that, unlike GFT, it is independent of the parameters k and k′. Secondly, our data structure can be constructed in O(nlog ^1+ε n) time and space, where 0<ε<1. The only price we pay is a slight increase, i.e. an additional log log n term, in the query time. Preliminary version appeared in [29]. C.S. Iliopoulos is supported by EPSRC and Royal Society grants. M.S. Rahman is supported by the Commonwealth Scholarship Commission in the UK under the Commonwealth Scholarship and Fellowship Plan (CSFP). M.S. Rahman is on leave from Department of CSE, BUET, Dhaka 1000, Bangladesh.     

A Fast Algorithm for the Path 2-Packing Problem

Let G be an undirected graph and $\mathcal{T}=\{T_{1},\ldots,T_{k}\}Let G be an undirected graph and T={T₁,?,T_k}\mathcal{T}=\{T_{1},\ldots,T_{k}\} be a collection of disjoint subsets of nodes. Nodes in T ₁∪⋅⋅⋅∪T _k are called terminals, other nodes are called inner. By a T\mathcal{T} -path we mean a path P such that P connects terminals from distinct sets in T\mathcal{T} and all internal nodes of P are inner. We study the problem of finding a maximum cardinality collection ℘ of T\mathcal{T} -paths such that at most two paths in ℘ pass through any node. Our algorithm is purely combinatorial and has the time complexity O(mn ²), where n and m denote the numbers of nodes and edges in G, respectively.     

The individual ergodic theorem on the IF-events with product

The ergodic theory and particularly the individual ergodic theorem were studied in many structures. Recently the individual ergodic theorem has been proved for MV-algebras of fuzzy sets (Riečan in Czech Math J 50(125):673–680, 2000; Riečan and Neubrunn in Integral, measure, and ordering. Kluwer, Dordrecht, 1997) and even in general MV-algebras (Jurečková in Int J Theor Phys 39:757–764, 2000). The notion of almost everywhere equality of observables was introduced by Riečan and Jurečková (Int J Theor Phys 44:1587–1597, 2005). They proved that the limit of Cesaro means is an invariant observable for P-observables. In Lendelová (Int J Theor Phys 45(5):915–923, 2006c) showed that the assumption of P-observable can be omitted. In this paper we prove the individual ergodic theorem on family of IF-events and show that each P {\mathcal{P}} -preserving transformation in this family can be expressed by two corresponding P^\flat,P^\sharp {\mathcal{P}}^\flat,{\mathcal{P}}^\sharp -preserving transformations in tribe T. {\mathcal{T}}.     

Linear-Time Recognition of Helly Circular-Arc Models and Graphs

A circular-arc model ℳ is a circle C together with a collection A\mathcal{A} of arcs of C. If A\mathcal{A} satisfies the Helly Property then ℳ is a Helly circular-arc model. A (Helly) circular-arc graph is the intersection graph of a (Helly) circular-arc model. Circular-arc graphs and their subclasses have been the object of a great deal of attention in the literature. Linear-time recognition algorithms have been described both for the general class and for some of its subclasses. However, for Helly circular-arc graphs, the best recognition algorithm is that by Gavril, whose complexity is O(n ³). In this article, we describe different characterizations for Helly circular-arc graphs, including a characterization by forbidden induced subgraphs for the class. The characterizations lead to a linear-time recognition algorithm for recognizing graphs of this class. The algorithm also produces certificates for a negative answer, by exhibiting a forbidden subgraph of it, within this same bound.     

A Sequential Algorithm for Generating Random Graphs

We present a nearly-linear time algorithm for counting and randomly generating simple graphs with a given degree sequence in a certain range. For degree sequence (d _i ) _i=1 ⁿ with maximum degree d _max?=O(m ^1/4?τ ), our algorithm generates almost uniform random graphs with that degree sequence in time O(md _max?) where $m=\frac{1}{2}\sum_{i}d_{i}We present a nearly-linear time algorithm for counting and randomly generating simple graphs with a given degree sequence in a certain range. For degree sequence (d _i ) _i=1 ⁿ with maximum degree d _max=O(m ^1/4−τ ), our algorithm generates almost uniform random graphs with that degree sequence in time O(md _max) where m=\frac12?_id_im=\frac{1}{2}\sum_{i}d_{i} is the number of edges in the graph and τ is any positive constant. The fastest known algorithm for uniform generation of these graphs (McKay and Wormald in J. Algorithms 11(1):52–67, 1990) has a running time of O(m ² d _max²). Our method also gives an independent proof of McKay’s estimate (McKay in Ars Combinatoria A 19:15–25, 1985) for the number of such graphs.     

Quadratic Kernelization for Convex Recoloring of Trees

The Convex Recoloring (CR) problem measures how far a tree of characters differs from exhibiting a so-called “perfect phylogeny”. For an input consisting of a vertex-colored tree T, the problem is to determine whether recoloring at most k vertices can achieve a convex coloring, meaning by this a coloring where each color class induces a subtree. The problem was introduced by Moran and Snir (J. Comput. Syst. Sci. 73:1078–1089, 2007; J. Comput. Syst. Sci. 74:850–869, 2008) who showed that CR is NP-hard, and described a search-tree based FPT algorithm with a running time of O(k(k/log k) ^k n ⁴). The Moran and Snir result did not provide any nontrivial kernelization. In this paper, we show that CR has a kernel of size O(k ²).     

Space Efficient Dynamic Orthogonal Range Reporting

In this paper we present new space efficient dynamic data structures for orthogonal range reporting. The described data structures support planar range reporting queries in time O(log n+klog log (4n/(k+1))) and space O(nlog log n), or in time O(log n+k) and space O(nlog  ^ε n) for any ε>0. Both data structures can be constructed in O(nlog n) time and support insert and delete operations in amortized time O(log ² n) and O(log nlog log n) respectively. These results match the corresponding upper space bounds of Chazelle (SIAM J. Comput. 17, 427–462, 1988) for the static case. We also present a dynamic data structure for d-dimensional range reporting with search time O(log  ^d−1 n+k), update time O(log  ^d n), and space O(nlog  ^d−2+ε n) for any ε>0. The model of computation used in our paper is a unit cost RAM with word size log n. A preliminary version of this paper appeared in the Proceedings of the 21st Annual ACM Symposium on Computational Geometry 2005. Work partially supported by IST grant 14036 (RAND-APX).     

Applying Modular Decomposition to Parameterized Cluster Editing Problems

A graph G is said to be a bicluster graph if G is a disjoint union of bicliques (complete bipartite subgraphs), and a cluster graph if G is a disjoint union of cliques (complete subgraphs). In this work, we study the parameterized versions of the NP-hard Bicluster Graph Editing and Cluster Graph Editing problems. The former consists of obtaining a bicluster graph by making the minimum number of modifications in the edge set of an input bipartite graph. When at most k modifications are allowed (Bicluster(k) Graph Editing problem), this problem is FPT, and can be solved in O(4 ^k nm) time by a standard search tree algorithm. We develop an algorithm of time complexity O(4 ^k +n+m), which uses a strategy based on modular decomposition techniques; we slightly generalize the original problem as the input graph is not necessarily bipartite. The algorithm first builds a problem kernel with O(k ²) vertices in O(n+m) time, and then applies a bounded search tree. We also show how this strategy based on modular decomposition leads to a new way of obtaining a problem kernel with O(k ²) vertices for the Cluster(k) Graph Editing problem, in O(n+m) time. This problem consists of obtaining a cluster graph by modifying at most k edges in an input graph. A previous FPT algorithm of time O(1.92 ^k +n ³) for this problem was presented by Gramm et al. (Theory Comput. Syst. 38(4), 373–392, 2005, Algorithmica 39(4), 321–347, 2004). In their solution, a problem kernel with O(k ²) vertices is built in O(n ³) time.     

Solving MAX-<Emphasis Type="Italic">r</Emphasis>-SAT Above a Tight Lower Bound

We present an exact algorithm that decides, for every fixed r≥2 in time O(m)+2^O(k2)O(m)+2^{O(k^{2})} whether a given multiset of m clauses of size r admits a truth assignment that satisfies at least ((2 ^r −1)m+k)/2 ^r clauses. Thus Max-r-Sat is fixed-parameter tractable when parameterized by the number of satisfied clauses above the tight lower bound (1−2^−r )m. This solves an open problem of Mahajan et al. (J. Comput. Syst. Sci. 75(2):137–153, 2009).     

Model Checking Weighted Integer Reset Timed Automata

Weighted timed automata (WTA), introduced in Alur et al. (Proceedings of HSCC’01, LNCS, vol. 2034, pp. 49–62, Springer, Berlin, 2001), Behrmann et al. (Proceedings of HSCC’01, LNCS, vol. 2034, pp. 147–161, Springer, Berlin, 2001) are an extension of Alur and Dill (Theor. Comput. Sci. 126(2):183–235, 1994) timed automata, a widely accepted formalism for the modelling and verification of real time systems. Weighted timed automata extend timed automata by allowing costs on the locations and edges. There has been a lot of interest Bouyer et al. (Inf. Process. Lett. 98(5):188–194, 2006), Bouyer et al. (Log. Methods Comput. Sci. 4(2):9, 2008), Brihaye et al. (Proceedings of FORMATS/FTRTFT’04, LNCS, vol. 3253, pp. 277–292, Springer, Berlin, 2004), Brihaye et al. (Inf. Comput. 204(3):408–433, 2006) in studying the model checking problem of weighted timed automata. The properties of interest are written using logic weighted CTL (WCTL), an extension of CTL with costs. It has been shown Bouyer et al. (Log. Methods Comput. Sci. 4(2):9, 2008) that the problem of model checking WTAs with a single clock using WCTL with no external cost variables is decidable, while 3 clocks render the problem undecidable Bouyer et al. (Inf. Process. Lett. 98(5):188–194, 2006). The question of 2 clocks is open. In this paper, we introduce a subclass of weighted timed automata called weighted integer reset timed automata (WIRTA) and study the model checking problem. We give a clock reduction technique for WIRTA. Given a WIRTA A\mathcal{A} with n≥1 clocks, we show that a single clock WIRTA A￠\mathcal{A}' preserving the paths and costs of A\mathcal{A} can be obtained. This gives us the decidability of model checking WIRTA with n≥1 clocks and m≥1 costs using WCTL with no external cost variables. We then show that for a restricted version of WCTL with external cost variables, the model checking problem is undecidable for WIRTA with 3 stopwatch costs and 1 clock. Finally, we show that model checking WTA with 2 clocks and 1 stopwatch cost against WCTL with no external cost variables is undecidable, thereby answering a question that has remained long open.     

A Note on Exact Algorithms for Vertex Ordering Problems on Graphs

In this note, we give a proof that several vertex ordering problems can be solved in O ^∗(2 ⁿ ) time and O ^∗(2 ⁿ ) space, or in O ^∗(4 ⁿ ) time and polynomial space. The algorithms generalize algorithms for the Travelling Salesman Problem by Held and Karp (J. Soc. Ind. Appl. Math. 10:196–210, 1962) and Gurevich and Shelah (SIAM J. Comput. 16:486–502, 1987). We survey a number of vertex ordering problems to which the results apply.     

Maximizing the weighted number of just-in-time jobs in?several two-machine scheduling systems

The problem of maximizing the weighted number of just-in-time jobs in a two-machine flow shop scheduling system is known to be NP\mathcal {NP}-hard (Choi and Yoon in J. Shed. 10:237–243, 2007). However, the question of whether this problem is strongly or ordinarily NP\mathcal{NP}-hard remains an open question. We provide a pseudo-polynomial time algorithm to solve this problem, proving that it is NP\mathcal{NP}-hard in the ordinary sense. Moreover, we show how the pseudo-polynomial algorithm can be converted to a fully polynomial time approximation scheme (FPTAS). In addition, we prove that the same problem is strongly NP\mathcal{NP}-hard for both a two-machine job shop scheduling system and a two-machine open shop scheduling system.     

Applying Approximate Counting for Computing the Frequency Moments of Long Data Streams

This paper takes up a remark in the well-known paper of Alon, Matias, and Szegedy (J. Comput. Syst. Sci. 58(1):137–147, 1999) about the computation of the frequency moments of data streams and shows in detail how any F _k with k≥1 can be approximately computed using space O(km ^1−1/k (k+log m+log log  n)) based on approximate counting. An important building block for this, which may be interesting in its own right, is a new approximate variant of reservoir sampling using space O(log log  n) for constant error parameters.