On Minimum Edge Ranking Spanning Trees

In this paper, we introduce the problem of computing a minimum edge ranking spanning tree (MERST); i.e., find a spanning tree of a given graph G whose edge ranking is minimum. Although the minimum edge ranking of a given tree can be computed in polynomial time, we show that problem MERST is NP-hard. Furthermore, we present an approximation algorithm for MERST, which realizes its worst case performance ratio where n is the number of vertices in G and Δ* is the maximum degree of a spanning tree whose maximum degree is minimum. Although the approximation algorithm is a combination of two existing algorithms for the restricted spanning tree problem and for the minimum edge ranking problem of trees, the analysis is based on novel properties of the edge ranking of trees.     

Approximate labelled subtree homeomorphism

Given two undirected trees T and P, the Subtree Homeomorphism Problem is to find whether T has a subtree t that can be transformed into P by removing entire subtrees, as well as repeatedly removing a degree-2 node and adding the edge joining its two neighbors. In this paper we extend the Subtree Homeomorphism Problem to a new optimization problem by enriching the subtree-comparison with node-to-node similarity scores. The new problem, called Approximate Labelled Subtree Homeomorphism (ALSH), is to compute the homeomorphic subtree of T which also maximizes the overall node-to-node resemblance. We describe an O(m²n/logm+mnlogn) algorithm for solving ALSH on unordered, unrooted trees, where m and n are the number of vertices in P and T, respectively. We also give an O(mn) algorithm for rooted ordered trees and O(mnlogm) and O(mn) algorithms for unrooted cyclically ordered and unrooted linearly ordered trees, respectively.     

O(n2.5) time algorithms for the subgraph homeomorphism problem on trees

The complexity of the subgraph homeomorphism problems have been open. We show O(n^2.5) time algorithms when the problems are restricted to trees, directed or undirected. The algorithm can be applied to the subtree isomorphism problem for unrooted trees with the same complexity, and improves over Reyner's O(n^3.5) algorithm for the subtree isomorphism problem.     

Improved processor bounds for combinatorial problems in RNC

Our main result improves the known processor bound by a factor ofn ⁴ (maintaining the expected parallel running time,O(log³ n)) for the following important problem:find a perfect matching in a general or in a bipartite graph with n vertices. A solution to that problem is used in parallel algorithms for several combinatorial problems, in particular for the problems of finding i) a (perfect) matching of maximum weight, ii) a maximum cardinality matching, iii) a matching of maximum vertex weight, iv) a maximums-t flow in a digraph with unit edge capacities. Consequently the known algorithms for those problems are substantially improved.The results of this paper have been presented at the 26-th Annual IEEE Symp. FOCS, Portland, Oregon (October 1985).Partially supported by NSF Grants MCS 8303139 and DCR 8511713.Supporeted by NSF Grants MCS 8203232 and DCR 8507573.     

Faster Subtree Isomorphism

We study the subtree isomorphism problem: Given trees H and G, find a subtree of G which is isomorphic to H or decide that there is no such subtree. We give an O((k^1.5/log k)n)-time algorithm for this problem, where k and n are the number of vertices in H and G, respectively. This improves over the O(k^1.5n) algorithms of Chung and Matula. We also give a randomized (Las Vegas) O(k^1.376n)-time algorithm for the decision problem.     

Alternating cycle-free matchings

The investigation of alternating cycle-free matchings is motivated by the Jump-number problem for partially ordered sets and the problem of counting maximum cardinality matchings in hexagonal systems.We show that the problem of deciding whether a given chordal bipartite graph has an alternating cycle-free matching of a given cardinality is NP-complete. A weaker result, for bipartite graphs only, has been known for some time. Also, the alternating cycle-free matching problem remains NP-complete for strongly chordal split graphs of diameter 2.In contrast, we give algorithms to solve the alternating cycle-free matching problem in polynomial time for bipartite distance hereditary graphs (time O(m ²) on graphs with m edges) and distance hereditary graphs (time O(m ⁵)).     

Distributed near-optimal matching

In this paper, we consider the following distributed bipartite matching problem: LetG=(L,R;E) be a bipartite graph in which boys are partL (left nodes), and girls are partR (right nodes.) There is an edge(l _i ,r _j )E iff boyl _i is interested in girlr _j . Every boyl _i will propose to a girlr _j among all those he is interested in, i.e., his adjacent right nodes in the bipartite graphG. If several boys propose to the same girl, only one of them will be accepted by the girl. We assume that none of the boys communicate with others. This matching problem is typical of distributed computing under incomplete information: Each boy only knows his own preference but none of the others. We first study the one-round matching problem: each boy proposes to at most one girl, so that the total number of girls receiving a proposal is maximized. If the maximum matching isM, then no deterministic algorithm can produce a matching of size not bounded by a constant, but a randomized algorithm achieves — and this is shown optimal by an adversary argument. If we allow many rounds in matching, with the senders learning from their failures, then, for deterministic algorithms, the ratio (of the optimal solution to the solution of the algorithm) is unbounded when the number of rounds is smaller than (G), and becomes bounded (two) at the (G)-th round. In contrast, an extension of the one-round randomized algorithm establishes that there is no such discontinuity in the randomized case. This randomized result is also matched by an upper bound of asymptotically the same order.     

On the shape of the fringe of various types of random trees

We analyze a fringe tree parameter w in a variety of settings, utilizing a variety of methods from the analysis of algorithms and data structures. Given a tree t and one of its leaves a, the w(t, a) parameter denotes the number of internal nodes in the subtree rooted at a's father. The closely related w?(t, a) parameter denotes the number of leaves, excluding a, in the subtree rooted at a's father. We define the cumulative w parameter as W(t) = Σ_aw(t, a), i.e. as the sum of w(t, a) over all leaves a of t. The w parameter not only plays an important rôle in the analysis of the Lempel–Ziv '77 data compression algorithm, but it is captivating from a combinatorial viewpoint too. In this report, we determine the asymptotic behavior of the w and W parameters on a variety of types of trees. In particular, we analyze simply generated trees, recursive trees, binary search trees, digital search trees, tries and Patricia tries. The final section of this report briefly summarizes and improves the previously known results about the w? parameter's behavior on tries and suffix trees, originally published in one author's thesis (see Analysis of the multiplicity matching parameter in suffix trees. Ph.D. Thesis, Purdue University, West Lafayette, IN, U.S.A., May 2005; Discrete Math. Theoret. Comput. Sci. 2005; AD :307–322; IEEE Trans. Inform. Theory 2007; 53 :1799–1813). This survey of new results about the w parameter is very instructive since a variety of different combinatorial methods are used in tandem to carry out the analysis. Copyright © 2008 John Wiley & Sons, Ltd.     

Transversal hypergraphs to perfect matchings in bipartite graphs: Characterization and generation algorithms

A minimal blocker in a bipartite graph G is a minimal set of edges the removal of which leaves no perfect matching in G. We give an explicit characterization of the minimal blockers of a bipartite graph G. This result allows us to obtain a polynomial delay algorithm for finding all minimal blockers of a given bipartite graph. Equivalently, we obtain a polynomial delay algorithm for listing the anti‐vertices of the perfect matching polytope of G. We also provide generation algorithms for other related problems, including d‐factors in bipartite graphs, and perfect 2‐matchings in general graphs. © 2006 Wiley Periodicals, Inc. J Graph Theory 53: 209–232, 2006     

Minimum Color Sum of Bipartite Graphs

The problem ofminimum color sumof a graph is to color the vertices of the graph such that the sum (average) of all assigned colors is minimum. Recently it was shown that in general graphs this problem cannot be approximated withinn^{1 − ε}, for any ε > 0, unlessNP = ZPP(Bar-Noyet al., Information and Computation140(1998), 183–202). In the same paper, a 9/8-approximation algorithm was presented for bipartite graphs. The hardness question for this problem on bipartite graphs was left open. In this paper we show that the minimum color sum problem for bipartite graphs admits no polynomial approximation scheme, unlessP = NP. The proof is byL-reducing the problem of finding the maximum independent set in a graph whose maximum degree is four to this problem. This result indicates clearly that the minimum color sum problem is much harder than the traditional coloring problem, which is trivially solvable in bipartite graphs. As for the approximation ratio, we make a further step toward finding the precise threshold. We present a polynomial 10/9-approximation algorithm. Our algorithm uses a flow procedure in addition to the maximum independent set procedure used in previous solutions.     

A maximum stable matching for the roommates problem

The stable roommates problem is that of matchingn people inton/2 disjoint pairs so that no two persons, who are not paired together, both prefer each other to their respective mates under the matching. Such a matching is called a complete stable matching. It is known that a complete stable matching may not exist. Irving proposed anO(n ²) algorithm that would find one complete stable matching if there is one, or would report that none exists. Since there may not exist any complete stable matching, it is natural to consider the problem of finding a maximum stable matching, i.e., a maximum number of disjoint pairs of persons such that these pairs are stable among themselves. In this paper, we present anO(n ²) algorithm, which is a modified version of Irving's algorithm, that finds a maximum stable matching.This research was supported by National Science Council of Republic of China under grant NSC 79-0408-E009-04.     

Matchings in superpositions of (n,n)-bipartite trees

Pick two trees from among all “bipartite trees” with a fixed (n, n) two-coloring. We estimate the probability that the superposition of these two trees contains a perfect matching. As n →∞, this probability approaches 1. © 1994 John Wiley & Sons, Inc.     

Approximating the minimum clique cover and other hard problems in subtree filament graphs

Subtree filament graphs are the intersection graphs of subtree filaments in a tree. This class of graphs contains subtree overlap graphs, interval filament graphs, chordal graphs, circle graphs, circular-arc graphs, cocomparability graphs, and polygon-circle graphs. In this paper we show that, for circle graphs, the clique cover problem is NP-complete and the h-clique cover problem for fixed h is solvable in polynomial time. We then present a general scheme for developing approximation algorithms for subtree filament graphs, and give approximation algorithms developed from the scheme for the following problems which are NP-complete on circle graphs and therefore on subtree filament graphs: clique cover, vertex colouring, maximum k-colourable subgraph, and maximum h-coverable subgraph.     

Expected time complexity of the auction algorithm and the push relabel algorithm for maximum bipartite matching on random graphs

In this paper we analyze the expected time complexity of the auction algorithm for the matching problem on random bipartite graphs. We first prove that if for every non‐maximum matching on graph G there exist an augmenting path with a length of at most 2l + 1 then the auction algorithm converges after N ? l iterations at most. Then, we prove that the expected time complexity of the auction algorithm for bipartite matching on random graphs with edge probability and c > 1 is w.h.p. This time complexity is equal to other augmenting path algorithms such as the HK algorithm. Furthermore, we show that the algorithm can be implemented on parallel machines with processors and shared memory with an expected time complexity of . © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 48, 384–395, 2016     

Connected matchings in chordal bipartite graphs

A connected matching in a graph is a collection of edges that are pairwise disjoint but joined by another edge of the graph. Motivated by applications to Hadwiger’s conjecture, Plummer, Stiebitz, and Toft (2003) introduced connected matchings and proved that, given a positive integer $k$, determining whether a graph has a connected matching of size at least $k$ is NP-complete. Cameron (2003) proved that this problem remains NP-complete on bipartite graphs, but can be solved in polynomial-time on chordal graphs. We present a polynomial-time algorithm that finds a maximum connected matching in a chordal bipartite graph. This includes a novel edge-without-vertex-elimination ordering of independent interest. We give several applications of the algorithm, including computing the Hadwiger number of a chordal bipartite graph, solving the unit-time bipartite margin-shop scheduling problem in the case in which the bipartite complement of the precedence graph is chordal bipartite, and determining–in a totally balanced binary matrix–the largest size of a square sub-matrix that is permutation equivalent to a matrix with all zero entries above the main diagonal.     

Matching subsequences in trees

Given two rooted, labeled trees P and T the tree path subsequence problem is to determine which paths in P are subsequences of which paths in T. Here a path begins at the root and ends at a leaf. In this paper we propose this problem as a useful query primitive for XML data, and provide new algorithms improving the previously best known time and space bounds.     

Tree-edges deletion problems with bounded diameter obstruction sets

We study the following problem: given a tree G and a finite set of trees H, find a subset O of the edges of G such that G-O does not contain a subtree isomorphic to a tree from H, and O has minimum cardinality. We give sharp boundaries on the tractability of this problem: the problem is polynomial when all the trees in H have diameter at most 5, while it is NP-hard when all the trees in H have diameter at most 6. We also show that the problem is polynomial when every tree in H has at most one vertex with degree more than 2, while it is NP-hard when the trees in H can have two such vertices.The polynomial-time algorithms use a variation of a known technique for solving graph problems. While the standard technique is based on defining an equivalence relation on graphs, we define a quasiorder. This new variation might be useful for giving more efficient algorithm for other graph problems.     

Primal separation for 0/1 polytopes

 The 0/1 primal separation problem is: Given an extreme point xˉ of a 0/1 polytope P and some point x ^*, find an inequality which is tight at xˉ, violated by x ^* and valid for P or assert that no such inequality exists. It is known that this separation variant can be reduced to the standard separation problem for P. We show that 0/1 optimization and 0/1 primal separation are polynomial time equivalent. This implies that the problems 0/1 optimization, 0/1 standard separation, 0/1 augmentation, and 0/1 primal separation are polynomial time equivalent. Then we provide polynomial time primal separation procedures for matching, stable set, maximum cut, and maximum bipartite graph problems, giving evidence that these algorithms are conceptually simpler and easier to implement than their corresponding counterparts for standard separation. In particular, for perfect matching we present an algorithm for primal separation that rests only on simple max-flow computations. In contrast, the known standard separation method relies on an explicit minimum odd cut algorithm. Consequently, we obtain a very simple proof that a maximum weight perfect matching of a graph can be computed in polynomial time. Received: August 20, 2001 / Accepted: April 2002 Published online: December 9, 2002 RID="⋆" ID="⋆" This research was developed while the author was on leave at the Istituto di Analisi dei Sistemi ed Informatica, Viale Manzoni 30, 00185 Roma, supported by the project TMR-DONET nr. ERB FMRX-CT98-0202 of the European Union. Mathematics Subject Classification (2000): 90C10, 90C60, 90C57     

Approximation Algorithms for Pick-and-Place Robots

In this paper we study the problem of finding placement tours for pick-and-place robots, also known as the printed circuit board assembly problem with m positions on a board, n bins containing m components and n locations for the bins. In the standard model where the working time of the robot is proportional to the distances travelled, the general problem appears as a combination of the travelling salesman problem and the matching problem, and for m=n we have an Euclidean, bipartite travelling salesman problem. We give a polynomial-time algorithm which achieves an approximation guarantee of 3+. An important special instance of the problem is the case of a fixed assignment of bins to bin-locations. This appears as a special case of a bipartite TSP satisfying the quadrangle inequality and given some fixed matching arcs. We obtain a 1.8 factor approximation with the stacker crane algorithm of Frederikson, Hecht and Kim. For the general bipartite case we also show a 2.0 factor approximation algorithm which is based on a new insertion technique for bipartite TSPs with quadrangle inequality. Implementations and experiments on real-world as well as random point configurations conclude this paper.     

On the use of suboptimal matchings for scaling and ordering sparse symmetric matrices

The use of matchings is a powerful technique for scaling and ordering sparse matrices prior to the solution of a linear system Ax = b. Traditional methods such as implemented by the HSL software package MC64 use the Hungarian algorithm to solve the maximum weight maximum cardinality matching problem. However, with advances in the algorithms and hardware used by direct methods for the parallelization of the factorization and solve phases, the serial Hungarian algorithm can represent an unacceptably large proportion of the total solution time for such solvers. Recently, auction algorithms and approximation algorithms have been suggested as alternatives for achieving near‐optimal solutions for the maximum weight maximum cardinality matching problem. In this paper, the efficacy of auction and approximation algorithms as replacements for the Hungarian algorithm is assessed in the context of sparse symmetric direct solvers when used in problems arising from a range of practical applications. High‐cardinality suboptimal matchings are shown to be as effective as optimal matchings for the purposes of scaling. However, matching‐based ordering techniques require that matchings are much closer to optimality before they become effective. The auction algorithm is demonstrated to be capable of finding such matchings significantly faster than the Hungarian algorithm, but our ‐approximation matching approach fails to consistently achieve a sufficient cardinality. Copyright © 2015 The Authors Numerical Linear Algebra with Applications Published by John Wiley & Sons Ltd.