An Edge-Splitting Algorithm in Planar Graphs

For a multigraph G = (V, E), let s V be a designated vertex which has an even degree, and let _G (V – s) denote min{c _G(X) | Ø X V – s}, where c _G(X) denotes the size of cut X. Splitting two adjacent edges (s, u) and (s, v) means deleting these edges and adding a new edge (u, v). For an integer k, splitting two edges e ₁ and e ₂ incident to s is called (k, s)-feasible if _G(V – s) k holds in the resulting graph G. In this paper, we prove that, for a planar graph G and an even k or k = 3 with k _G (V – s), there exists a complete (k, s)-feasible splitting at s such that the resulting graph G is still planar, and present an O(n ³ log n) time algorithm for finding such a splitting, where n = |V|. However, for every odd k 5, there is a planar graph G with a vertex s which has no complete (k, s)-feasible and planarity-preserving splitting. As an application of this result, we show that for an outerplanar graph G and an even integer k the problem of optimally augmenting G to a k-edge-connected planar graph can be solved in O(n ³ log n) time.     

The Independence Number of Graphs with a Forbidden Cycle and Ramsey Numbers

Let k 5 be a fixed integer and let m = (k – 1)/2. It is shown that the independence number of a C _k-free graph is at least c ₁[ d(v)^{1/(m – 1)}]^{(m – 1)/m} and that, for odd k, the Ramsey number r(C _k, K _n) is at most c ₂(n ^{m + 1}/log n)^1/m , where c ₁ = c ₁(m) > 0 and c ₂ = c ₂(m) > 0.     

Power Assignment for <Emphasis Type="Italic">k</Emphasis>-Connectivity in Wireless Ad Hoc Networks

The problem Min-Power k-Connectivity seeks a power assignment to the nodes in a given wireless ad hoc network such that the produced network topology is k-connected and the total power is the lowest. In this paper, we present several approximation algorithms for this problem. Specifically, we propose a 3k-approximation algorithm for any k, a (k + 12H (k)) -approximation algorithm for k(2k–1) n where n is the network size, a (k+2(k + 1)/2) -approximation algorithm for 2 k7, a 6-approximation algorithm for k = 3, and a 9-approximation algorithm for k = 4.This work is supported in part by Hong Kong Research Grant Council under grant No. CityU 1149/04E.This work is partially supported by NSF CCR-0311174.     

On Combinatorial Approximation of Covering 0-1 Integer Programs and Partial Set Cover

The problems dealt with in this paper are generalizations of the set cover problem, min{cx | Ax b, x {0,1}ⁿ}, where c Q₊ⁿ, A {0,1}^{m × n}, b 1. The covering 0-1 integer program is the one, in this formulation, with arbitrary nonnegative entries of A and b, while the partial set cover problem requires only m–K constrains (or more) in Ax b to be satisfied when integer K is additionall specified. While many approximation algorithms have been recently developed for these problems and their special cases, using computationally rather expensive (albeit polynomial) LP-rounding (or SDP-rounding), we present a more efficient purely combinatorial algorithm and investigate its approximation capability for them. It will be shown that, when compared with the best performance known today and obtained by rounding methods, although its performance comes short in some special cases, it is at least equally good in general, extends for partial vertex cover, and improves for weighted multicover, partial set cover, and further generalizations.     

Context in the Risk Assessment of Digital Systems

As the use of digital computers for instrumentation and control of safety-critical systems has increased, there has been a growing debate over the issue of whether probabilistic risk assessment techniques can be applied to these systems. This debate has centered on the issue of whether software failures can be modeled probabilistically. This paper describes a context-based approach to software risk assessment that explicitly recognizes the fact that the behavior of software is not probabilistic. The source of the perceived uncertainty in its behavior results from both the input to the software as well as the application and environment in which the software is operating. Failures occur as the result of encountering some context for which the software was not properly designed, as opposed to the software simply failing randomly. The paper elaborates on the concept of error-forcing context as it applies to software. It also illustrates a methodology which utilizes event trees, fault trees, and the Dynamic Flowgraph Methodology (DFM) to identify error-forcing contexts for software in the form of fault tree prime implicants.     

A Further Improved Approximation Algorithm for Breakpoint Graph Decomposition

Breakpoint graph decomposition is a crucial step in all recent approximation algorithms for SORTING BY REVERSALS, which is one of the best-known algorithmic problems in computational molecular biology. Caprara and Rizzi recently improved the approximation ratio for breakpoint graph decomposition from to + 1.4348 + , for any positive . In this paper, we extend the techniques of Caprara and Rizzi and incorporate a balancing argument to further improve the approximation ratio to + 1.4193 + , for any positive . These improvements imply improved approximation results for SORTING BY REVERSALS for almost all random permutations.     

Comments on the Paper: Attacking the Market Split Problem with Lattice Point Enumeration

We present a few comments on the paper Attacking the market split problem with lattice point enumeration by A. Wasserman, published in Journal of Combinatorial Optimization, vol. 6, pp. 5–16, 2002.     

Generalized Diameters and Rabin Numbers of Networks

Reliability and efficiency are important criteria in the design of interconnection networks. Recently, the w-wide diameter d_w(G), the (w – 1)-fault diameter D_w(G), and the w-Rabin number r_w(G) have been used to measure network reliability and efficiency. In this paper, we study d_w(G), D_w(G) and r_w(G) using the strong w-Rabin number r_w ^*(G) for 1 w k(G) and G is a circulant network G(d_n; {1, d,..., d^{n –1}}), a d-ary cube network C(d, n), a generalized hypercube GH(m_{n – 1},..., m0), a folded hypercube FH(n) or a WK-recursive network WK(d, t).     

Algorithm for the Cost Edge-Coloring of Trees

Let C be a set of colors, and let be a cost function which assigns a real number (c) to each color C in C. An edge-coloring of a graph G is to color all the edges of G so that any two adjacent edges are colored with different colors. In this paper we give an efficient algorithm to find an optimal edge-coloring of a given tree T, that is, an edge-coloring f of T such that the sum of costs (f(e)) of colors f(e) assigned to all edges e is minimum among all edge-colorings of T. The algorithm takes time O(n²) if n is the number of vertices and is the maximum degree of T.     

On Shortest k-Edge-Connected Steiner Networks in Metric Spaces

Given a set of points P in a metric space, let l(P) denote the ratio of lengths between the shortest k-edge-connected Steiner network and the shortest k-edge-connected spanning network on P, and let r = inf l(P) P for k 1. In this paper, we show that in any metric space, r 3/4 for k 2, and there exists a polynomial-time -approximation for the shortest k-edge-connected Steiner network, where = 2 for even k and = 2 + 4/(3k) for odd k. In the Euclidean plane, and .     

Improved Dynamic Programming in Connection with an FPTAS for the Knapsack Problem

A vector merging problem is introduced where two vectors of length n are merged such that the k-th entry of the new vector is the minimum over of the -th entry of the first vector plus the sum of the first k – + 1 entries of the second vector. For this problem a new algorithm with O(n log n) running time is presented thus improving upon the straightforward O(n ²) time bound.The vector merging problem can appear in different settings of dynamic programming. In particular, it is applied for a recent fully polynomial time approximation scheme (FPTAS) for the classical 0–1 knapsack problem by the same authors.     

Center and Distinguisher for Strings with Unbounded Alphabet

Consider two sets and of strings of length L with characters from an unbounded alphabet , i.e., the size of is not bounded by a constant and has to be taken into consideration as a parameter for input size. A closest string s* of is a string that minimizes the maximum of Hamming¹ distance(s, s*) over all string s : s . In contrast, a farthest string t* from maximizes the minimum of Hamming distance(t*,t) over all elements t: t . A distinguisher of from is a string that is close to every string in and far away from any string in . We obtain polynomial time approximation schemes to settle the above problems.     

On Approximability of Boolean Formula Minimization

For a Boolean function given by a Boolean formula (or a binary circuit) S we discuss the problem of building a Boolean formula (binary circuit) of minimal size, which computes the function g equivalent to , or -equivalent to , i.e., . In this paper we prove that if P NP then this problem can not be approximated with a good approximation ratio by a polynomial time algorithm.     

Fast On-Line/Off-Line Algorithms for Optimal Reinforcement of a Network and its Connections with Principal Partition

The problem of computing the strength and performing optimal reinforcement for an edge-weighted graph G(V, E, w) is well-studied. In this paper, we present fast (sequential linear time and parallel logarithmic time) on-line algorithms for optimally reinforcing the graph when the reinforcement material is available continuously on-line. These are the first on-line algorithms for this problem. We invest O(|V|³|E|log|V|) time (equivalent to (|V|) invocations of the fastest known algorithms for optimal reinforcement) in preprocessing the graph before the start of our algorithms. It is shown that the output of our on-line algorithms is as good as that of the off-line algorithms. Thus our algorithms are better than the fastest off-line algorithms in situations when a sequence of more than (|V|) reinforcement problems need to be solved. The key idea is to make use of ideas underlying the theory of Principal Partition of a Graph. Our ideas are easily generalized to the general setting of polymatroid functions. We also present a new efficient algorithm for computation of the Principal Sequence of a graph.     

Geometry of Semidefinite Max-Cut Relaxations via Matrix Ranks

Semidefinite programming (SDP) relaxations are proving to be a powerful tool for finding tight bounds for hard discrete optimization problems. This is especially true for one of the easier NP-hard problems, the Max-Cut problem (MC). The well-known SDP relaxation for Max-Cut, here denoted SDP1, can be derived by a first lifting into matrix space and has been shown to be excellent both in theory and in practice.Recently the present authors have derived a new relaxation using a second lifting. This new relaxation, denoted SDP2, is strictly tighter than the relaxation obtained by adding all the triangle inequalities to the well-known relaxation. In this paper we present new results that further describe the remarkable tightness of this new relaxation. Let denote the feasible set of SDP2 for the complete graph with n nodes, let F _n denote the appropriately defined projection of into , the space of real symmetric n × n matrices, and let C _n denote the cut polytope in . Further let be the matrix variable of the SDP2 relaxation and X F _n be its projection. Then for the complete graph on 3 nodes, F ₃ = C ₃ holds. We prove that the rank of the matrix variable of SDP2 completely characterizes the dimension of the face of the cut polytope in which the corresponding matrix X lies. This shows explicitly the connection between the rank of the variable Y of the second lifting and the possible locations of the projected matrix X within C ₃. The results we prove for n = 3 cast further light on how SDP2 captures all the structure of C ₃, and furthermore they are stepping stones for studying the general case n 4. For this case, we show that the characterization of the vertices of the cut polytope via rank Y = 1 extends to all n 4. More interestingly, we show that the characterization of the one-dimensional faces via rank Y = 2 also holds for n 4. Furthermore, we prove that if rank Y = 2 for n 3, then a simple algorithm exhibits the two rank-one matrices (corresponding to cuts) which are the vertices of the one-dimensional face of the cut polytope where X lies.     

Efficient Heuristics for Orientation Metric and Euclidean Steiner Tree Problems

We consider Steiner minimum trees (SMT) in the plane, where only orientations with angle , 0 i – 1 and an integer, are allowed. The orientations define a metric, called the orientation metric, , in a natural way. In particular, ₂ metric is the rectilinear metric and the Euclidean metric can beregarded as metric. In this paper, we provide a method to find an optimal SMT for 3 or 4 points by analyzing the topology of SMT's in great details. Utilizing these results and based on the idea of loop detection first proposed in Chao and Hsu, IEEE Trans. CAD, vol. 13, no. 3, pp. 303–309, 1994, we further develop an O(n²) time heuristic for the general SMT problem, including the Euclidean metric. Experiments performed on publicly available benchmark data for 12 different metrics, plus the Euclidean metric, demonstrate the efficiency of our algorithms and the quality of our results.     

Local Optimality and Its Application on Independent Sets for k-claw Free Graphs

Given a graph G = (V,E), we define the locally optimal independent sets asfollows. Let S be an independent set and T be a subset of V such that S T = and (S) T, where (S) is defined as the neighbor set of S. A minimum dominating set of S in T is defined as T_D(S) T such that every vertex of S is adjacent to a vertex inTD(S) and TD(S) has minimum cardinality. An independent setI is called r-locally optimal if it is maximal and there exists noindependent set S V\I with |ID (S)| r such that|S| >|I (S)|.In this paper, we demonstrate that for k-claw free graphs ther-locally optimal independent sets is found in polynomial timeand the worst case is bounded by , where I and I* are a locally optimal and an optimal independent set,respectively. This improves the best published bound by Hochbaum (1983) bynearly a factor of two. The bound is proved by LP duality and complementaryslackness. We provide an efficientO(|V|^r+3) algorithm to find an independent set which is notnecessarily r-locally optimal but is guarantteed with the above bound. Wealso present an algorithm to find a r-locally optimal independent set inO(|V|^r(k-1)+3) time.     

On Approximate Graph Colouring and MAX-k-CUT Algorithms Based on the θ-Function

The problem of colouring a k-colourable graph is well-known to be NP-complete, for k 3. The MAX-k-CUT approach to approximate k-colouring is to assign k colours to all of the vertices in polynomial time such that the fraction of `defect edges' (with endpoints of the same colour) is provably small. The best known approximation was obtained by Frieze and Jerrum (1997), using a semidefinite programming (SDP) relaxation which is related to the Lovász -function. In a related work, Karger et al. (1998) devised approximation algorithms for colouring k-colourable graphs exactly in polynomial time with as few colours as possible. They also used an SDP relaxation related to the -function.In this paper we further explore semidefinite programming relaxations where graph colouring is viewed as a satisfiability problem, as considered in De Klerk et al. (2000). We first show that the approximation to the chromatic number suggested in De Klerk et al. (2000) is bounded from above by the Lovász -function. The underlying semidefinite programming relaxation in De Klerk et al. (2000) involves a lifting of the approximation space, which in turn suggests a provably good MAX-k-CUT algorithm. We show that of our algorithm is closely related to that of Frieze and Jerrum; thus we can sharpen their approximation guarantees for MAX-k-CUT for small fixed values of k. For example, if k = 3 we can improve their bound from 0.832718 to 0.836008, and for k = 4 from 0.850301 to 0.857487. We also give a new asymptotic analysis of the Frieze-Jerrum rounding scheme, that provides a unifying proof of the main results of both Frieze and Jerrum (1997) and Karger et al. (1998) for k 0.     

Approximating the Independence Number and the Chromatic Number in Expected Polynomial Time

The independence number of a graph and its chromatic number are known to be hard to approximate. Due to recent complexity results, unless coRP = NP, there is no polynomial time algorithm which approximates any of these quantities within a factor of n ^1– for graphs on n vertices.We show that the situation is significantly better for the average case. For every edge probability p = p(n) in the range n ^–1/2+ p 3/4, we present an approximation algorithm for the independence number of graphs on n vertices, whose approximation ratio is O((np)^1/2/log n) and whose expected running time over the probability space G(n, p) is polynomial. An algorithm with similar features is described also for the chromatic number.A key ingredient in the analysis of both algorithms is a new large deviation inequality for eigenvalues of random matrices, obtained through an application of Talagrand's inequality.     

A comparative study of U.S. and Iraqi students

This study uses a sample comprised of U.S. students and Iraqi students to determine if differences occur over ethical perceptions based on cultural/demographic issues. Irrespective of demographics, the results of this study indicate significant cultural differences between Iraqi students and American students with regard to selected ethical issues concerning graduate education. Specifically the differences occurred in the students' perceptions of winning is everything, selling one's soul, logic before emotion, and pander to professors. Iraqi students consistently viewed these beliefs as more necessary for success in their graduate education than did their American counterparts.