Computing rectangle enclosures

The rectangle enclosure problem is the problem of determining the subset of n iso-oriented planar rectangles that enclose a query rectangle Q. In this paper, we use a three layered data structure which is a combination of Range and Priority search trees and answers both the static and dynamic cases of the problem. Both the cases use O(n> log² n) space. For the static case, the query time is O(log² n log log n + K). The dynamic case is supported in O(log³ n + K) query time using O(log³ n) amortized time per update. K denotes the size of the answer. For the d-dimensional space the results are analogous. The query time is O(log^2d-2 n log log n + K) for the static case and O(log^2d-1 n + K) for the dynamic case. The space used is O(n> log^2d-2 n) and the amortized time for an update is O(log^2d-1 n). The existing bounds given for a class of problems which includes the present one, are O(log^2d n + K) query time, O(log^2d n) time for an insertion and O(log^2d-1 n) time for a deletion.     

Loopless generation of up–down permutations

An up–down permutation P=(p₁,p₂,…,p_n) is a permutation of the integers 1 to n which satisfies constraints specified by a sequence C=(c₁,c₂,…,c_n−1) of U's and D's of length n−1. If c_i is U then p_i<p_i+1 otherwise p_i−1>p_i. A loopless algorithm is developed for generating all the up–down permutations satisfying any sequence C. Ranking and unranking algorithms are discussed.     

The generalized column incidence graph and a matroid base-listing algorithm

The generalized column incidence graph of a matroid base is defined, and it is shown that all elements on a minimal path in this graph lie in a common circuit. Also, an algorithm is provided which lists all bases of a matroid and calculates the Whitney and Tutte polynomials. The complexity of this algorithm is shown to be O(mN(n- m)(c(M) + m)), where Mis a matroid of rank mon a set of cardinality nNis the number of bases of M, and c(M) is the complexity of checking independence in M.     

General polynomial roots and their multiplicities in O(N)memory and O(N2)Time

For a given real or complex polynomial p of degree n we modify the Euclidean algorithm to find a general tridiagonal matrix representation T of the monic version of p and then use the tridiagonal DQR eigenvalue algorithm on T in order to find

all roots ofp with their multiplicities in O(n²) operations

and 0(n) storage. We include details of the implementation and comparisons with several, standard and recent, essentially 0(n³) polynomial root finders.     

On the multisearching problem for hypercubes

In this paper we give improved bounds for the multisearch problem on a hypercube. This is a parallel search problem where the elements in the structure S to be searched are totally ordered, but where it is not possible to compare in constant time any two given queries q and q′. More precisely, we are given on a n-processor hypercube a sorted n-element sequence S, and a set Q of n queries, and we need to find for each query q Q its location in the sorted S. We present an improved algorithm for the multisearch problem, one that takes O(log n(log log n)³) time on a n-processor hypercube. This problem is fundamental in computational geometry, for example it models planar point location in a slab. We give as application a trapezoidal decomposition algorithm with the same time complexity on a n log n-processor hypercube. The hypercube model for which we claim our bounds is the standard one, SIMD, with O(1) memory registers per processor, and with one-port communication. Each register can store O(log n) bits, so that a processor knows its ID.     

Continuous bottleneck tree partitioning problems

We study continuous partitioning problems on tree network spaces whose edges and nodes are points in Euclidean spaces. A continuous partition of this space into p connected components is a collection of p subtrees, such that no pair of them intersect at more than one point, and their union is the tree space. An edge-partition is a continuous partition defined by selecting p−1 cut points along the edges of the underlying tree, which is assumed to have n nodes. These cut points induce a partition into p subtrees (connected components). The objective is to minimize (maximize) the maximum (minimum) “size” of the components (the min–max (max–min) problem). When the size is the length of a subtree, the min–max and the max–min partitioning problems are NP-hard. We present O(n² log(min(p,n))) algorithms for the edge-partitioning versions of the problem. When the size is the diameter, the min–max problems coincide with the continuous p-center problem. We describe O(n log³ n) and O(n log² n) algorithms for the max–min partitioning and edge-partitioning problems, respectively, where the size is the diameter of a component.     

Prime power divisors of binomial coefficients

It is known that for sufficiently large n and m and any r the binomial coefficient (ⁿ_m) which is close to the middle coefficient is divisible by p^r where p is a ‘large’ prime. We prove the exact divisibility of (ⁿ_m) by p^r for p> c(n). The lower bound is essentially the best possible. We also prove some other results on divisibility of binomial coefficients.     

具有时间与位置相关的两类平行机排序问题

研究带有维修时间限制的时间和位置效应平行机排序问题,涉及同型机和非同类机两种机器类型.工件的实际加工时间同时受到位置效应和时间效应影响,且机器具有维修限制.目标函数由机器负载,总完工时间与总等待时间组成.非同类机情形下,通过将排序问题转化为指派问题,给出多项式时间算法,其算法的时间复杂度为O（n^k+2/（k-1）!）.同型机情形下通过转化目标函数,使用匹配算法得出排序问题的多项式时间解,其时间复杂度为O（（2n+m+n log n）n^k-1/（k-1）!）.     

Holes in random graphs

It is shown that for every >0 with the probability tending to 1 as n→∞ a random graph G(n,p) contains induced cycles of all lengths k, 3 ≤ k ≤ (1 − )n log c/c, provided c(n) = (n − 1)p(n)→∞.     

A faster 2-approximation algorithm for the minmax p-traveling salesmen problem on a tree

Given an edge-weighted tree T and an integer p1, the minmax p-traveling salesmen problem on a tree T asks to find p tours such that the union of the p tours covers all the vertices. The objective is to minimize the maximum of length of the p tours. It is known that the problem is NP-hard and has a (2−2/(p+1))-approximation algorithm which runs in O(p^p−1n^p−1) time for a tree with n vertices. In this paper, we consider an extension of the problem in which the set of vertices to be covered now can be chosen as a subset S of vertices and weights to process vertices in S are also introduced in the tour length. For the problem, we give an approximation algorithm that has the same performance guarantee, but runs in O((p−1)!·n) time.     

A solvable case of the variance minimization problem

An algorithm is derived, which solves the completion time variance (CTV) problem with equal processing times in O(n log n) time. This result indicates that the special case formulated by Merten and Muller [1] is well solvable.     

On the number of edge-disjoint one factors and the existence of k-factors in complete multipartite graphs

In this paper we use Tutte's f-factor theorem and the method of amalgamations to find necessary and sufficient conditions for the existence of a k-factor in the complete multipartite graph K(p(1), …, p(n)), conditions that are reminiscent of the Erdös-Gallai conditions for the existence of simple graphs with a given degree sequence. We then use this result to investigate the maximum number of edge-disjoint 1-factors in K(p(1), …, p(n)), settling the problem in the case where this number is greater than δ - p(2), where p(1) p(2) … p(n).     

On-line construction of the upper envelope of triangles and surface patches in three dimensions

In this paper, we describe a randomized incremental algorithm for computing the upper envelope (i.e., the pointwise maximum) of a set of n triangles in three dimensions. This algorithm is an on-line algorithm. It is structure-sensitive: the expected cost of inserting the n-th triangle is O(log nΣ_r=1ⁿτ(r)/r²) and depends on the expected size τ(r) of an intermediate result for r triangles. Since τ(r) can be Θ(r²(r)) in the worst case, this cost is bounded in the worst case by O(n(n) log n). (The expected behaviour is analyzed by averaging over all possible orderings of the input.) The main new characteristics is the use of a two-level history graph. (The history graph is an auxiliary data structure maintained by randomized incremental algorithms.) Our algorithm is fairly simple and appears to be efficient in practice. It extends to surfaces and surface patches of fixed maximum algebraic degree.     

Further results on irregular, critical perfect systems of difference sets II: systems without splits

An (m, n; u, v; c)-system is a collection of components, m of valency u−1 and n of valency v−1, whose difference sets form a perfect system with threshold c. If there is an (m, n; 3, 6; c)-system, then m2c−1; and if there is a (2c−1, n; 3, 6; c)-system, then 2c−1n. For all sufficiently large c, there are (2c−1, n; 3, 6; c)-systems with a split at 3c+6n−1 at least when n=1, 5, 6 and 7, but such systems do not exist for n=2, 3 or 4.

We describe here a general method of construction for (2c−1, n; 3, 6; c)-systems and use it to show that there are such systems for 2n4 and certain values of c depending on n. We also discuss the limitations of this method.     

On ringeisen's isolation game

We develop the theory of the Isolation Game on a graph G, in which two players alternately “switch” at successive vertices v not previously switched. The switching operation deletes all edges incident with v, and creates new edges between v and those vertices not previously adjacent to it. The game is won when a vertex is first isolated. Among other results, we show that n-vertex forced wins exist for all n, and that length-p forced wins exist for all p. We give generic examples of forced wins which (against best defense) can be won only very late in the game. We also prove several large classes of graphs to be unwinnable, and give a complexity results for a problem closely related to the identification of drawing strategies in I_n(G).     

Orthochronous subgroups of O(p,q)

The matrices if O(p,q) whose upper left p × p corners have positive determinant form a subgroup of O(p,q).     

Landmarks in graphs

Navigation can be studied in a graph-structured framework in which the navigating agent (which we shall assume to be a point robot) moves from node to node of a “graph space”. The robot can locate itself by the presence of distinctively labeled “landmark” nodes in the graph space. For a robot navigating in Euclidean space, visual detection of a distinctive landmark provides information about the direction to the landmark, and allows the robot to determine its position by triangulation. On a graph, however, there is neither the concept of direction nor that of visibility. Instead, we shall assume that a robot navigating on a graph can sense the distances to a set of landmarks.

Evidently, if the robot knows its distances to a sufficiently large set of landmarks, its position on the graph is uniquely determined. This suggests the following problem: given a graph, what are the fewest number of landmarks needed, and where should they be located, so that the distances to the landmarks uniquely determine the robot's position on the graph? This is actually a classical problem about metric spaces. A minimum set of landmarks which uniquely determine the robot's position is called a “metric basis”, and the minimum number of landmarks is called the “metric dimension” of the graph. In this paper we present some results about this problem. Our main new results are that the metric dimension of a graph with n nodes can be approximated in polynomial time within a factor of O(log n), and some properties of graphs with metric dimension two.     

3-D vertical ray shooting and 2-D point enclosure, range searching, and arc shooting amidst convex fat objects

We present a new data structure for a set of n convex simply-shaped fat objects in the plane, and use it to obtain efficient and rather simple solutions to several problems including (i) vertical ray shooting—preprocess a set of n non-intersecting convex simply-shaped flat objects in 3-space, whose xy-projections are fat, for efficient vertical ray shooting queries, (ii) point enclosure—preprocess a set C of n convex simply-shaped fat objects in the plane, so that the k objects containing a query point p can be reported efficiently, (iii) bounded-size range searching— preprocess a set C of n convex fat polygons, so that the k objects intersecting a “not-too-large” query polygon can be reported efficiently, and (iv) bounded-size segment shooting—preprocess a set C as in (iii), so that the first object (if exists) hit by a “not-too-long” oriented query segment can be found efficiently. For the first three problems we construct data structures of size O(λ_s(n)log³n), where s is the maximum number of intersections between the boundaries of the (xy-projections) of any pair of objects, and λ_s(n) is the maximum length of (n, s) Davenport-Schinzel sequences. The data structure for the fourth problem is of size O(λ_s(n)log²n). The query time in the first problem is O(log⁴n), the query time in the second and third problems is O(log³n + klog²n), and the query time in the fourth problem is O(log³n).

We also present a simple algorithm for computing a depth order for a set as in (i), that is based on the solution to the vertical ray shooting problem. (A depth order for , if exists, is a linear order of , such that, if K₁, K₂ and K₁ lies vertically above K₂, then K₁ precedes K₂.) Unlike the algorithm of Agarwal et al. (1995) that might output a false order when a depth order does not exist, the new algorithm is able to determine whether such an order exists, and it is often more efficient in practical situations than the former algorithm.     

Subsets of an interval whose product is a power

We form squares from the product of integers in a short interval [n, n + t_n], where we include n in the product. If p is prime, p|n, and (₂^p) > n, we prove that p is the minimum t_n. If no such prime exists, we prove t_n √5n when n> 32. If n = p(2p − 1) and both p and 2p − 1 are primes, then t_n = 3p> 3 √n/2. For n(n + u) a square > n², we conjecture that a and b exist where n < a < b < n + u and nab is a square (except n = 8 and N = 392). Let g₂(n) be minimal such that a square can be formed as the product of distinct integers from [n, g₂(n)] so that no pair of consecutive integers is omitted. We prove that g₂(n) 3n − 3, and list or conjecture the values of g₂(n) for all n. We describe the generalization to kth powers and conjecture the values for large n.     

Polynomial algorithms for (integral) maximum two-flows in vertex edge-capacitated planar graphs

In this paper we study the maximum two-flow problem in vertex- and edge-capacitated undirected ST₂-planar graphs, that is, planar graphs where the vertices of each terminal pair are on the same face. For such graphs we provide an O(n) algorithm for finding a minimum two-cut and an O(n log n) algorithm for determining a maximum two-flow and show that the value of a maximum two-flow equals the value of a minimum two-cut. We further show that the flow obtained is half-integral and provide a characterization of edge and vertex capacitated ST₂-planar graphs that guarantees a maximum two-flow that is integral. By a simple variation of our maximum two-flow algorithm we then develop, for ST₂-planar graphs with vertex and edge capacities, an O(n log n) algorithm for determining an integral maximum two-flow of value not less than the value of a maximum two-flow minus one.