A hybrid algorithm for finding thekth smallest ofn elements in O(n) time

The problem of finding thekth smallest ofn elements can be solved either with O(n) algorithms or with O(n ²) algorithms. Although they require a higher number of operations in the worst case, O(n ²) algorithms are generally preferred to O(n) algorithms because of their better average performance. We present a hybrid algorithm which is O(n) in the worst case and efficient in the average case.     

A polynomial time primal network simplex algorithm for minimum cost flows

Developing a polynomial time primal network simplex algorithm for the minimum cost flow problem has been a long standing open problem. In this paper, we develop one such algorithm that runs in O(min(n ²m lognC, n ²m² logn)) time, wheren is the number of nodes in the network,m is the number of arcs, andC denotes the maximum absolute arc costs if arc costs are integer and ∞ otherwise. We first introduce a pseudopolynomial variant of the network simplex algorithm called the “premultiplier algorithm”. We then develop a cost-scaling version of the premultiplier algorithm that solves the minimum cost flow problem in O(min(nm lognC, nm ² logn)) pivots. With certain simple data structures, the average time per pivot can be shown to be O(n). We also show that the diameter of the network polytope is O(nm logn).     

Visibility with Multiple Reflections

We show that the region lit by a point light source inside a simple n -gon after at most k reflections off the boundary has combinatorial complexity O(n ^2k ) , for any k≥ 1 . A lower bound of Ω ((n/k-Θ(1)) ^2k ) is also established which matches the upper bound for any fixed k . A simple near-optimal algorithm for computing the illuminated region is presented, which runs in O(n ^2k log n) time and O(n ^2k ) space for k>1 , and in O(n ² log ² n) time and O(n ² ) space for k=1 . Received March 14, 1996, and in revised form December 22, 1997, and January 5, 1998.     

On-line coloringk-colorable graphs

We show that for anyk, there exists an on-line algorithm that will color anyk-colorable graph onn vertices withO(n ^1−1/k! ) colors. This improves the previous best upper bound ofO(nlog^(2k−3) n/log^(2k−4) n) due to Lovász, Saks, and Trotter. In the special casesk=3 andk=4 we obtain on-line algorithms that useO(n ^2/3log^1/3 n) andO(n ^5/6log^1/6 n) colors, respectively.     

New Similarity Measures between Polylines with Applications to Morphing and Polygon Sweeping

   Abstract. We introduce two new related metrics, the geodesic width and the link width , for measuring the ``distance' between two nonintersecting polylines in the plane. If the two polylines have n vertices in total, we present algorithms to compute the geodesic width of the two polylines in O(n <sup>2</sup> log n) time using O(n <sup>2</sup> ) space and the link width in O(n <sup>3</sup> log n) time using O(n <sup>2</sup> ) working space where n is the total number of edges of the polylines. Our computation of these metrics relies on two closely related combinatorial strutures: the shortest-path diagram and the link diagram of a simple polygon. The shortest-path (resp., link) diagram encodes the Euclidean (resp., link) shortest path distance between all pairs of points on the boundary of the polygon. We use these algorithms to solve two problems: • Compute a continuous transformation that ``morphs' one polyline into another polyline. Our morphing strategies ensure that each point on a polyline moves as little as necessary during the morphing, that every intermediate polyline is also simple and disjoint to any other intermediate polyline, and that no portion of the polylines to be morphed is stretched or compressed by more than a user-defined parameter during the entire morphing. We present an algorithm that computes the geodesic width of the two polylines and utilizes it to construct a corresponding morphing strategy in O(n ² log ² n) time using O(n ² ) space. We also give an O(nlog n) time algorithm to compute a 2-approximation of the geodesic width and a corresponding morphing scheme. • Locate a continuously moving target using a group of guards moving inside a simple polygon. The guards always determine a simple polygonal chain within the polygon, with consecutive guards along the chain being mutually visible. We compute a strategy that sweeps such a chain of guards through the polygon in order to locate a target. We compute in O(n ³ ) time and O(n ² ) working space the minimum number r ^* of guards needed to sweep an n -vertex polygon. We also give an approximation algorithm, using O(n log n) time and O(n) space, to compute an integer r such that max(r - 16, 2)≤ r ^* ≤ r and P can be swept with a chain of r guards.     

Algorithms for shortest paths and d-cycle problems

Let G be a weighted graph with n vertices and m edges. We address the d-cycle problem, i.e., the problem of finding a subgraph of minimum weight with given cyclomatic number d. Hartvigsen [Minimum path bases, J. Algorithms 15 (1993) 125–142] presented an algorithm with running time O(n²m) and O(n^2d−1m²) for the cyclomatic numbers d=1 and d2, respectively. Using a (d+1)-shortest-paths algorithm, we develop a new more efficient algorithm for the d-cycle problem with running time O(n^2d−1+n²m+n³logn).     

A fast algorithm for computing minimum 3-way and 4-way cuts

For an edge-weighted graph G with n vertices and m edges, we present a new deterministic algorithm for computing a minimum k-way cut for k=3,4. The algorithm runs in O(n ^k-1 F(n,m))=O(mn ^k log(n ² /m)) time and O(n ²) space for k=3,4, where F(n,m) denotes the time bound required to solve the maximum flow problem in G. The bound for k=3 matches the current best deterministic bound ?(mn ³) for weighted graphs, but improves the bound ?(mn ³) to O(n ² F(n,m))=O(min{mn ^8/3,m ^3/2 n ²}) for unweighted graphs. The bound ?(mn ⁴) for k=4 improves the previous best randomized bound ?(n ⁶) (for m=o(n ²)). The algorithm is then generalized to the problem of finding a minimum 3-way cut in a symmetric submodular system. Received: April 1999 / Accepted: February 2000?Published online August 18, 2000     

New Similarity Measures between Polylines with Applications to Morphing and Polygon Sweeping

Abstract. We introduce two new related metrics, the geodesic width and the link width , for measuring the ``distance' between two nonintersecting polylines in the plane. If the two polylines have n vertices in total, we present algorithms to compute the geodesic width of the two polylines in O(n <sup>2</sup> log n) time using O(n <sup>2</sup> ) space and the link width in O(n <sup>3</sup> log n) time using O(n <sup>2</sup> ) working space where n is the total number of edges of the polylines. Our computation of these metrics relies on two closely related combinatorial strutures: the shortest-path diagram and the link diagram of a simple polygon. The shortest-path (resp., link) diagram encodes the Euclidean (resp., link) shortest path distance between all pairs of points on the boundary of the polygon. We use these algorithms to solve two problems: • Compute a continuous transformation that ``morphs' one polyline into another polyline. Our morphing strategies ensure that each point on a polyline moves as little as necessary during the morphing, that every intermediate polyline is also simple and disjoint to any other intermediate polyline, and that no portion of the polylines to be morphed is stretched or compressed by more than a user-defined parameter during the entire morphing. We present an algorithm that computes the geodesic width of the two polylines and utilizes it to construct a corresponding morphing strategy in O(n ² log ² n) time using O(n ² ) space. We also give an O(nlog n) time algorithm to compute a 2-approximation of the geodesic width and a corresponding morphing scheme. • Locate a continuously moving target using a group of guards moving inside a simple polygon. The guards always determine a simple polygonal chain within the polygon, with consecutive guards along the chain being mutually visible. We compute a strategy that sweeps such a chain of guards through the polygon in order to locate a target. We compute in O(n ³ ) time and O(n ² ) working space the minimum number r ^* of guards needed to sweep an n -vertex polygon. We also give an approximation algorithm, using O(n log n) time and O(n) space, to compute an integer r such that max(r - 16, 2)≤ r ^* ≤ r and P can be swept with a chain of r guards.     

Computing Mixed Discriminants, Mixed Volumes, and Permanents

We construct a probabilistic polynomial time algorithm that computes the mixed discriminant of given n positive definite matrices within a 2 ^O(n) factor. As a corollary, we show that the permanent of an nonnegative matrix and the mixed volume of n ellipsoids in R ⁿ can be computed within a 2 ^O(n) factor by probabilistic polynomial time algorithms. Since every convex body can be approximated by an ellipsoid, the last algorithm can be used for approximating in polynomial time the mixed volume of n convex bodies in R ⁿ within a factor n ^O(n) . Received July 10, 1995, and in revised form May 20, 1996.     

Combinatorial 5/6-approximation of Max Cut in graphs of maximum degree 3

The best approximation algorithm for Max Cut in graphs of maximum degree 3 uses semidefinite programming, has approximation ratio 0.9326, and its running time is Θ(n^3.5logn); but the best combinatorial algorithms have approximation ratio 4/5 only, achieved in O(n²) time [J.A. Bondy, S.C. Locke, J. Graph Theory 10 (1986) 477–504; E. Halperin, et al., J. Algorithms 53 (2004) 169–185]. Here we present an improved combinatorial approximation, which is a 5/6-approximation algorithm that runs in O(n²) time, perhaps improvable even to O(n). Our main tool is a new type of vertex decomposition for graphs of maximum degree 3.     

An Optimal Algorithm to Solve the All-Pairs Shortest Paths Problem on Permutation Graphs

In this paper we present an optimal algorithm to solve the all-pairs shortest path problem on permutation graphs with n vertices and m edges which runs in O(n ²) time. Using this algorithm, the average distance of a permutation graph can also be computed in O(n ²) time.     

On the complexity of a single cell in certain arrangements of surfaces related to motion planning

We obtain near-quadratic upper bounds on the maximum combinatorial complexity of a single cell in certain arrangements ofn surfaces in 3-space where the lower bound for this quantity is Ω(n ²) or slightly larger. We prove a theorem that identifies a collection of topological and combinatorial conditions for a set of surface patches in space, which make the complexity of a single cell in an arrangement induced by these surface patches near-quadratic. We apply this result to arrangements related to motion-planning problems of two types of robot systems with three degrees of freedom and also to a special type of arrangements of triangles in space. The complexity of the entire arrangement in each case that we study can be Θ(n ³) in the worst case, and our single-cell bounds are of the formO(n ² α(n)), O(n ² logn), orO(n ² α(n)logn). The only previously known similar bounds are for the considerably simpler arrangements of planes or of spheres in space, where the bounds are Θ(n) and Θ(n ²), respectively. For some of the arrangements that we study we derive near-quadratic-time algorithms to compute a single cell. A preliminary version of this paper has appeared inProc. 7th ACM Symposium on Computational Geometry, North Conway, NH, 1991, pp. 314–323.     

A new pivot selection rule for the network simplex algorithm

We present a new network simplex pivot selection rule, which we call theminimum ratio pivot rule, and analyze the worst-case complexity of the resulting network simplex algorithm. We consider networks withn nodes,m arcs, integral arc capacities and integral supplies/demands of nodes. We define a {0, 1}-valued penalty for each arc of the network. The minimum ratio pivot rule is to select that eligible arc as the entering arc whose addition to the basis creates a cycle with the minimum cost-to-penalty ratio. We show that the so-defined primal network simplex algorithm solves minimum cost flow problem within O(nΔ) pivots and in O(Δ(m + n logn)) time, whereΔ is any upper bound on the sum of all arc flows in every feasible flow. For assignment and shortest path problems, our algorithm runs in O(n ²) pivots and O(nm +n ² logn) time.     

A Baby Steps/Giant Steps Probabilistic Algorithm for Computing Roadmaps in Smooth Bounded Real Hypersurface

We consider the problem of constructing roadmaps of real algebraic sets. This problem was introduced by Canny to answer connectivity questions and solve motion planning problems. Given s polynomial equations with rational coefficients, of degree D in n variables, Canny’s algorithm has a Monte Carlo cost of sⁿlog(s)D^O(n2)s^{n}\log(s)D^{O(n^{2})} operations in ℚ; a deterministic version runs in time sⁿlog(s)D^O(n4)s^{n}\log(s)D^{O(n^{4})} . A subsequent improvement was due to Basu, Pollack, and Roy, with an algorithm of deterministic cost s^d+1D^O(n2)s^{d+1}D^{O(n^{2})} for the more general problem of computing roadmaps of a semi-algebraic set (d≤n is the dimension of an associated object).     

Recognition Algorithms for Orders of Small Width and Graphs of Small Dilworth Number

Partially ordered sets of small width and graphs of small Dilworth number have many interesting properties and have been well studied. Here we show that recognition of such orders and graphs can be done more efficiently than by using the well-known algorithms based on bipartite matching and matrix multiplication. In particular, we show that deciding deciding if an order has width k can be done in O(kn ²) time and whether a graph has Dilworth number k can be done in O(k ² n ²) time.For very small k we have even better results. We show that orders of width at most 3 can be recognized in O(n) time and of width at most 4 in O(nlog n).     

Packing algorithms for arborescences (and spanning trees) in capacitated graphs

In a digraph with real-valued edge capacities, we pack the greatest number of arborescences in time O(n ³m log(n ²/m)); the packing uses at mostm distinct arborescences. Heren andm denote the number of vertices and edges in the given graph, respectively. Similar results hold for integral packing: we pack the greatest number of arborescences in time O(min{n, logN}n ²m log(n ²/)) using at mostm + n – 2 distinct arborescences; hereN denotes the largest (integral) capacity of an edge. These resuts improve the best previous bounds for capacitated digraphs. The algorithm extends to several related problems, including packing spanning trees in an undirected capacitated graph, and covering such graphs by forests. The algorithm provides a new proof of Edmonds' theorem for arborescence packing, for both integral and real capacities, based on a laminar family of sets derived from the packing. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.     

A note on the complexity of minimum dominating set

The currently (asymptotically) fastest algorithm for minimum dominating set on graphs of n nodes is the trivial Ω(2ⁿ) algorithm which enumerates and checks all the subsets of nodes. In this paper we present a simple algorithm which solves this problem in O(1.81ⁿ) time.     

Geometric Pattern Matching in d -Dimensional Space

We show that, using the L _∞ metric, the minimum Hausdorff distance under translation between two point sets of cardinality n in d -dimensional space can be computed in time O(n ^(4d-2)/3 log ² n) for 3 < d 8, and in time O(n ^5d/4 log ² n) for any d > 8 . Thus we improve the previous time bound of O(n ^2d-2 log ² n) due to Chew and Kedem. For d=3 we obtain a better result of O(n ³ log ² n) time by exploiting the fact that the union of n axis-parallel unit cubes can be decomposed into O(n) disjoint axis-parallel boxes. We prove that the number of different translations that achieve the minimum Hausdorff distance in d -space is . Furthermore, we present an algorithm which computes the minimum Hausdorff distance under the L ₂ metric in d -space in time , for any δ > 0. Received March 17, 1997, and in revised form January 19, 1998.     

The two-convex-polygons TSP: A solvable case

In this paper, the Travelling Salesman Problem whenm points are on one convex polygonP, andn points are on another convex polygonQ, insideP, is polynomially solved. For this specific case, anO(m ³ n ³) time andO(m ² n ²) space algorithm to obtain the tour with minimum length is provided.     

Parallel and superfast algorithms for Hankel systems of equations

Summary Utilizing kernel structure properties a unified construction of Hankel matrix inversion algorithms is presented. Three types of algorithms are obtained: 1)O(n ²) complexity Levinson type, 2)O (n) parallel complexity Schur-type, and 3)O(n log² n) complexity asymptotically fast ones. All algorithms work without additional assumption (like strong nonsingularity).