Augmenting a Submodular and Posi-modular Set Function by a Multigraph

Given a finite set V and a set function , we consider the problem of constructing an undirected multigraph G = (V,E) such that the cut function together has value at least 2 for all non-empty and proper subsets of V. If f is intersecting submodular and posi-modular, and satisfies the tripartite inequality, then we show that such a multigraph G with the minimum number of edges can be found in time, where is the time to compute the value of f(X) for a subset .     

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.     

A Probabilistic Analysis of the Capacitated Facility Location Problem

The solution value of a stochastic version of the capacitated facility location problem is studied. It is shown that, for large numbers of customers n, the value of can be closely approximated by , where the constant is identified as a function of the parameters of the underlying stochastic model. Furthermore, an extensive probabilistic analysis is performed on the difference that includes an exponential inequality on the tail distribution, a classification of the speed of convergence and a central limit theorem.     

Simple Approximation Algorithms for MAXNAESP and Hypergraph 2-colorability

Hypergraph 2-colorability, also known as set splitting, is a widely studied problem in graph theory. In this paper we study the maximization version of the same. We recast the problem as a special type of satisfiability problem and give approximation algorithms for it. Our results are valid for hypergraph 2-colorability, set splitting and MAX-CUT (which is a special case of hypergraph 2-colorability) because the reductions are approximation preserving. Here we study the MAXNAESP problem, the optimal solution to which is a truth assignment of the literals that maximizes the number of clauses satisfied. As a main result of the paper, we show that any locally optimal solution (a solution is locally optimal if its value cannot be increased by complementing assignments to literals and pairs of literals) is guaranteed a performance ratio of . This is an improvement over the ratio of attributed to another local improvement heuristic for MAX-CUT (C. Papadimitriou, Computational Complexity, Addison Wesley, 1994). In fact we provide a bound of for this problem, where k 3 is the minimum number of literals in a clause. Such locally optimal algorithms appear to subsume typical greedy algorithms that have been suggested for problems in the general domain of satisfiability. It should be noted that the NAESP problem where each clause has exactly two literals, is equivalent to MAX-CUT. However, obtaining good approximation ratios using semi-definite programming techniques (M. Goemans and D.P. Williamson, in Proceedings of the 26th Annual ACM Symposium on Theory of Computing, 1994a, pp. 422–431) appears difficult. Also, the randomized rounding algorithm as well as the simple randomized algorithm both (M. Goemans and D.P. Williamson, SIAM J. Disc. Math, vol. 7, pp. 656–666, 1994b) yield a bound of for the MAXNAESP problem. In contrast to this, the algorithm proposed in this paper obtains a bound of for this problem.     

Inverse Polymatroidal Flow Problem

Let D = (V, A) be a directed graph, for each vertex v V, let ⁺(v) and ^– (v) denote the sets of arcs leaving and entering v, and be intersecting families on ⁺(v) and ^–(v), respectively, and and be submodular functions on intersecting pairs. A flow f : A R is feasible if

A {{10}}-Approximation Algorithm for a Generalization of the Weighted Edge-Dominating Set Problem

We study the approximability of the weighted edge-dominating set problem. Although even the unweighted case is NP-Complete, in this case a solution of size at most twice the minimum can be efficiently computed due to its close relationship with minimum maximal matching; however, in the weighted case such a nice relationship is not known to exist. In this paper, after showing that weighted edge domination is as hard to approximate as the well studied weighted vertex cover problem, we consider a natural strategy, reducing edge-dominating set to edge cover. Our main result is a simple -approximation algorithm for the weighted edge-dominating set problem, improving the existing ratio, due to a simple reduction to weighted vertex cover, of 2r _WVC, where r _WVC is the approximation guarantee of any polynomial-time weighted vertex cover algorithm. The best value of r _WVC currently stands at . Furthermore we establish that the factor of is tight in the sense that it coincides with the integrality gap incurred by a natural linear programming relaxation of the problem.     

Facets of an Assignment Problem with 0–1 Side Constraint

We show that the problem of finding a perfect matching satisfying a single equality constraint with a 0–1 coefficients in an n × n incomplete bipartite graph, polynomially reduces to a special case of the same peoblem called the partitioned case. Finding a solution matching for the partitioned case in the incomlpete bipartite graph, is equivalent to minimizing a partial sum of the variables over = the convex hull of incidence vectors of solution matchings for the partitioned case in the complete bipartite graph. An important strategy to solve this minimization problem is to develop a polyhedral characterization of . Towards this effort, we present two large classes of valid inequalities for , which are proved to be facet inducing using a facet lifting scheme.     

Inverse Problems of Matroid Intersection

In this paper we study the inverse problem of matroid intersection: Two matroids M ₁ = (E, ₁) and M ₂ = (E, ₂), their intersection B, and a weight function w on E are given. We try to modify weight w, optimally and with bounds, such that B becomes a maximum weight intersection under the modified weight. It is shown in this paper that the problem can be formulated as a combinatorial linear program and can be further transformed into a minimum cost circulation problem. Hence it can be solved by strongly polynomial time algorithms. We also give a necessary and sufficient condition for the feasibility of the problem. Finally we extend the discussion to the version of the problem with Multiple Intersections.     

Tight Performance Bounds of CP-Scheduling on Out-Trees

The worst-case behavior of the critical path (CP) algorithm for multiprocessor scheduling with an out-tree task dependency structure is studied. The out-tree is not known in advance and the tasks are released on-line over time (each task is released at the completion time of its direct predecessor task in the out-tree). For each task, the processing time and the remainder (the length of the longest chain of the future tasks headed by this task) become known at its release time. The tight worst-case ratio and absolute error are derived for this strongly clairvoyant on-line model. For out-trees with a specific simple structure, essentially better worst-case ratio and absolute error are derived. Our bounds are given in terms of t _max, the length of the longest chain in the out-tree, and it is shown that the worst-case ratio asymptotically approaches 2 for large t _max when the number of processors , where is an integer close to . A non-clairvoyant on-line version (without knowledge of task processing time and remainder at the release time of the task) is also considered and is shown that the worst-case behavior of width-first search is better or the same as that of the depth-first search.     

Improved Approximation for Breakpoint Graph Decomposition and Sorting by Reversals

Sorting by Reversals (SBR) is one of the most widely studied models of genome rearrangements in computational molecular biology. At present, is the best known approximation ratio achievable in polynomial time for SBR. A very closely related problem, called Breakpoint Graph Decomposition (BGD), calls for a largest collection of edge disjoint cycles in a suitably-defined graph. It has been shown that for almost all instances SBR is equivalent to BGD, in the sense that any solution of the latter corresponds to a solution of the former having the same value. In this paper, we show how to improve the approximation ratio achievable in polynomial time for BGD, from the previously known to for any > 0. Combined with the results in (Caprara, Journal of Combinatorial Optimization, vol. 3, pp. 149–182, 1999b), this yields the same approximation guarantee for n! – O((n – 5)!) out of the n! instances of SBR on permutations with n elements. Our result uses the best known approximation algorithms for Stable Set on graphs with maximum degree 4 as well as for Set Packing where the maximum size of a set is 6. Any improvement in the ratio achieved by these approximation algorithms will yield an automatic improvement of our result.     

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.     

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.     

Approximation Algorithms in Batch Processing

A polynomial approximation scheme for minimizing makespan in a batch processing system under dynamic job arrivals is presented. A lower bound of on the competitive ratio of any on-line algorithm is proved. This is matched by an on-line algorithm for the special case of unbounded machine capacity.     

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.     

Minimum ε-equivalent Circuit Size Problem

For a Boolean function f given by its truth table (of length ) and a parameter s the problem considered is whether there is a Boolean function g -equivalent to f, i.e., , and computed by a circuit of size at most s. In this paper we investigate the complexity of this problem and show that for specific values of it is unlikely to be in P/poly. Under the same assumptions we also consider the optimization variant of the problem and prove its inapproximability.     

On the Complexity of Constructing Evolutionary Trees

In this paper we study a few important tree optimization problems with applications to computational biology. These problems ask for trees that are consistent with an as large part of the given data as possible. We show that the maximum homeomorphic agreement subtree problem cannot be approximated within a factor of , where N is the input size, for any 0 in polynomial time unless P = NP, even if all the given trees are of height 2. On the other hand, we present an O(N log N)-time heuristic for the restriction of this problem to instances with O(1) trees of height O(1) yielding solutions within a constant factor of the optimum. We prove that the maximum inferred consensus tree problem is NP-complete, and provide a simple, fast heuristic for it yielding solutions within one third of the optimum. We also present a more specialized polynomial-time heuristic for the maximum inferred local consensus tree problem.     

Improved Bounds on Relaxations of a Parallel Machine Scheduling Problem

We consider the problem of scheduling n jobs withrelease dates on m identical parallel machines to minimize the average completion time of the jobs. We prove that the ratio of the average completion time of the optimal nonpreemptive schedule to that of the optimal preemptive schedule is at most 7/3, improving a bound of Shmoys and Wein.     

The Steiner Tree Problem in Kalmanson Matrices and in Circulant Matrices

We investigate the computational complexity of two special cases of the Steiner tree problem where the distance matrix is a Kalmanson matrix or a circulant matrix, respectively. For Kalmanson matrices we develop an efficient polynomial time algorithm that is based on dynamic programming. For circulant matrices we give an -hardness proof and thus establish computational intractability.     

Construction of the nearest neighbor embracing graph of a point set

This paper gives optimal algorithms for the construction of the Nearest Neighbor Embracing Graph (NNE-graph) of a given point set V of size n in the k-dimensional space (k-D) for k = 2,3. The NNE-graph provides another way of connecting points in a communication network, which has lower expected degree at each point and shorter total length of connections with respect to those using Delaunay triangulation. In fact, the NNE-graph can also be used as a tool to test whether a point set is randomly generated or has some particular properties. We show that in 2-D the NNE-graph can be constructed in optimal time in the worst case. We also present an time algorithm, where d is the -th largest degree in the utput NNE-graph. The algorithm is optimal when . The algorithm is also sensitive to the structure of the NNE-graph, for instance when , the number of edges in NNE-graph is bounded by for any value g with . We finally propose an time algorithm for the problem in 3-D, where d and are the -th largest vertex degree and the largest vertex degree in the NNE-graph, respectively. The algorithm is optimal when the largest vertex degree of the NNE-graph is .