Space-efficient geometric divide-and-conquer algorithms

We develop a number of space-efficient tools including an approach to simulate divide-and-conquer space-efficiently, stably selecting and unselecting a subset from a sorted set, and computing the kth smallest element in one dimension from a multi-dimensional set that is sorted in another dimension. We then apply these tools to solve several geometric problems that have solutions using some form of divide-and-conquer. Specifically, we present a deterministic algorithm running in time using extra memory given inputs of size n for the closest pair problem and a randomized solution running in expected time and using extra space for the bichromatic closest pair problem. For the orthogonal line segment intersection problem, we solve the problem in time using extra space where n is the number of horizontal and vertical line segments and k is the number of intersections.     

求解二层规划问题的遗传算法

本文求解二层规划问题的遗传算法，给出了算法基本框架并对算法实现进行了研究．算法适用于各类线性和非线性二层规划问题．数值计算结果显示，该方法是可行和有效的．     

Fast and stable two‐way algorithm for diagonal plus semi‐separable systems of linear equations

An algorithm for the solution of linear systems of equations where the coefficient matrix is diagonal plus a semi‐separable matrix is considered. The algorithm is stable with linear complexity. Furthermore, it is suitable for an implementation on a system of two processors. Copyright © 2001 John Wiley & Sons, Ltd.     

A new approximation algorithm for the multilevel facility location problem

In this paper we propose a new integer programming formulation for the multilevel facility location problem and a novel 3-approximation algorithm based on LP-rounding. The linear program that we use has a polynomial number of variables and constraints, thus being more efficient than the one commonly used in the approximation algorithms for these types of problems.     

A new parallel chasing algorithm for transforming arrowhead matrices to tridiagonal form

Rutishauser, Gragg and Harrod and finally H.Y. Zha used the same class of chasing algorithms for transforming arrowhead matrices to tridiagonal form. Using a graphical theoretical approach, we propose a new chasing algorithm. Although this algorithm has the same sequential computational complexity and backward error properties as the old algorithms, it is better suited for a pipelined approach. The parallel algorithm for this new chasing method is described, with performance results on the Paragon and nCUBE. Comparison results between the old and the new algorithms are also presented.

     

Testing the diameter of graphs

We propose a general model for testing graph properties, which extends and simplifies the bounded degree model of Goldreich and Ron [Property Testing in Bounded Degree Graphs, Proc. 31st Annual ACM Symposium on the Theory of Computing, 1997, pp. 406–415.] In this model, we present a family of algorithms that test whether the diameter of a graph is bounded by a given parameter D, or is ?‐far from any graph with diameter at most β(D). The function β(D) ranges between D+4 and 4D+2, depending on the algorithm. All our algorithms run in time polynomial in 1/?. © 2002 Wiley Periodicals, Inc. Random Struct. Alg. 20: 165–183, 2002     

Searching for a subset of counterfeit coins: Randomization vs determinism and adaptiveness vs non‐adaptiveness

We are given n coins of which k are heavy (defective), while the remaining n ‐ k are light (good). We know both the weight of the good coins and the weight of the defective ones. Therefore, if we weigh a subset Q ? S with a spring scale, then the outcome will tell us exactly the number of defectives contained in Q. The problem, known as Counterfeit Coins problem, is to identify the set of defective coins by minimizing the number of weighings, also called queries. It is well known that Θ(klog _{k +1}(n/k)) queries are enough, even for non‐adaptive algorithms, in case k ≤ cn for some constant 0 < c < 1. A natural interesting generalization arises when we are required to identify any subset of m ≤ k defectives. We show that while for randomized algorithms \begin{align*}\tilde{\Theta}(m)\end{align*} queries are sufficient, the deterministic non‐adaptive counterpart still requires Θ(klog _{k +1}(n/k)) queries, in case k ≤ n/2⁸; therefore, finding any subset of defectives is not easier than finding all of them by a non‐adaptive deterministic algorithm. © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2012     

Multiple-Subarc Gradient-Restoration Algorithm, Part 1: Algorithm Structure

Rapid progresses in information and computer technology allow the development of more advanced optimal control algorithms dealing with real-world problems. In this paper, which is Part 1 of a two-part sequence, a multiple-subarc gradient-restoration algorithm (MSGRA) is developed. We note that the original version of the sequential gradient-restoration algorithm (SGRA) was developed by Miele et al. in single-subarc form (SSGRA) during the years 1968–86; it has been applied successfully to solve a large number of optimal control problems of atmospheric and space flight.MSGRA is an extension of SSGRA, the single-subarc gradient-restoration algorithm. The primary reason for MSGRA is to enhance the robustness of gradient-restoration algorithms and also to enlarge the field of applications. Indeed, MSGRA can be applied to optimal control problems involving multiple subsystems as well as discontinuities in the state and control variables at the interface between contiguous subsystems.Two features of MSGRA are increased automation and efficiency. The automation of MSGRA is enhanced via time normalization: the actual time domain is mapped into a normalized time domain such that the normalized time length of each subarc is 1. The efficiency of MSGRA is enhanced by using the method of particular solutions to solve the multipoint boundary-value problems associated with the gradient phase and the restoration phase of the algorithm.In a companion paper [Part 2 (Ref. 2)], MSGRA is applied to compute the optimal trajectory for a multistage launch vehicle design, specifically, a rocket-powered spacecraft ascending from the Earth surface to a low Earth orbit (LEO). Single-stage, double-stage, and triple-stage configurations are considered and compared.     

Mapping enthalpy-based solidification algorithms onto vector and parallel architectures

Effective methods are required to solve three-dimensional solidification problems with fine meshes. This paper considers some of the problems associated with mapping control volume-based enthalpy algorithms onto vector processors and transputer-based parallel networks. Although vector processors may bring speedups of a factor of 5 or so, it appears that transputer-based networks have the facility to yield speedups that increase linearly with the number of transputer chips used.     

A Taxonomy of Evolutionary Algorithms in Combinatorial Optimization

This paper shows how evolutionary algorithms can be described in a concise, yet comprehensive and accurate way. A classification scheme is introduced and presented in a tabular form called TEA (Table of Evolutionary Algorithms). It distinguishes between different classes of evolutionary algorithms (e.g., genetic algorithms, ant systems) by enumerating the fundamental ingredients of each of these algorithms. At the end, possible uses of the TEA are illustrated on classical evolutionary algorithms.     

Evolutionary Algorithms for the Vehicle Routing Problem with Time Windows

This paper surveys the research on evolutionary algorithms for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from a single depot to a set of geographically scattered points. The routes must be designed in such a way that each point is visited only once by exactly one vehicle within a given time interval. All routes start and end at the depot, and the total demands of all points on one particular route must not exceed the capacity of the vehicle. The main types of evolutionary algorithms for the VRPTW are genetic algorithms and evolution strategies. In addition to describing the basic features of each method, experimental results for the benchmark test problems of Solomon (1987) and Gehring and Homberger (1999) are presented and analyzed.     

Reconfiguration of connected graph partitions

Motivated by recent computational models for redistricting and detection of gerrymandering, we study the following problem on graph partitions. Given a graph $G$ and an integer $k\ge 1$, a $k$-district map of $G$ is a partition of $V\left(G\right)$ into $k$ nonempty subsets, called districts, each of which induces a connected subgraph of $G$. A switch is an operation that modifies a $k$-district map by reassigning a subset of vertices from one district to an adjacent district; a 1-switch is a switch that moves a single vertex. We study the connectivity of the configuration space of all $k$-district maps of a graph $G$ under 1-switch operations. We give a combinatorial characterization for the connectedness of this space that can be tested efficiently. We prove that it is PSPACE-complete to decide whether there exists a sequence of 1-switches that takes a given $k$-district map into another; and NP-hard to find the shortest such sequence (even if a sequence of polynomial lengths is known to exist). We also present efficient algorithms for computing a sequence of 1-switches that take a given $k$-district map into another when the space is connected, and show that these algorithms perform a worst-case optimal number of switches up to constant factors.     

On the convergence of a factorized distribution algorithm with truncation selection

We investigate the global convergence of a factorized distribution algorithm (FDA) with truncation selection. Like conventional genetic algorithms, FDAs maintain and successively improve a population of solutions. In FDAs, a distribution model is built based on the statistical information extracted from a set of selected solutions in the current population, and then the model thus built is used to generate new solutions for the next generation. The variable‐dependence structure of the distribution model in FDAs is determined by the variable‐interaction structure of the objective function. We prove that the FDA with truncation selection converges globally for optimization of a class of additively decomposable functions (ADF). Our results imply that the utilization of appropriately selected dependence relationships is sufficient to guarantee the global convergence of estimation of distribution algorithms (EDAs) for optimization of ADFs. © 2004 Wiley Periodicals, Inc. Complexity 9: 17–23, 2004     

High‐performance direct algorithms for computing the sign function of triangular matrices

Algorithms and implementations for computing the sign function of a triangular matrix are fundamental building blocks for computing the sign of arbitrary square real or complex matrices. We present novel recursive and cache‐efficient algorithms that are based on Higham's stabilized specialization of Parlett's substitution algorithm for computing the sign of a triangular matrix. We show that the new recursive algorithms are asymptotically optimal in terms of the number of cache misses that they generate. One algorithm that we present performs more arithmetic than the nonrecursive version, but this allows it to benefit from calling highly optimized matrix multiplication routines; the other performs the same number of operations as the nonrecursive version, suing custom computational kernels instead. We present implementations of both, as well as a cache‐efficient implementation of a block version of Parlett's algorithm. Our experiments demonstrate that the blocked and recursive versions are much faster than the previous algorithms and that the inertia strongly influences their relative performance, as predicted by our analysis.     

Randomized and quantum algorithms yield a speed-up for initial-value problems

Quantum algorithms and complexity have recently been studied not only for discrete, but also for some numerical problems. Most attention has been paid so far to the integration and approximation problems, for which a speed-up is shown in many important cases by quantum computers with respect to deterministic and randomized algorithms on a classical computer. In this paper, we deal with the randomized and quantum complexity of initial-value problems. For this nonlinear problem, we show that both randomized and quantum algorithms yield a speed-up over deterministic algorithms. Upper bounds on the complexity in the randomized and quantum settings are shown by constructing algorithms with a suitable cost, where the construction is based on integral information. Lower bounds result from the respective bounds for the integration problem.     

Divide and conquer algorithms for computing the eigendecomposition of symmetric diagonal-plus-semiseparable matrices

Three fast and stable divide and conquer algorithms to compute the eigendecomposition of symmetric diagonal-plus-semiseparable matrices are considered. AMS subject classification 15A18, 15A23, 65F15The research of the second and the third author was supported by the Research Council K.U. Leuven, to13.25cmproject OT/00/16 (SLAP: Structured Linear Algebra Package), by the Fund for Scientific Research –     

A better approximation algorithm for the budget prize collecting tree problem

Given an undirected graph G=(V,E), an edge cost c(e)?0 for each edge e∈E, a vertex prize p(v)?0 for each vertex v∈V, and an edge budget B. The BUDGET PRIZE COLLECTING TREE PROBLEM is to find a subtree T′=(V′,E′) that maximizes , subject to . We present a (4+ε)-approximation algorithm.     

Approximating Huffman codes in parallel

In this paper we present new results on the approximate parallel construction of Huffman codes. Our algorithm achieves linear work and logarithmic time, provided that the initial set of elements is sorted. This is the first parallel algorithm for that problem with the optimal time and work. Combining our approach with the best known parallel sorting algorithms we can construct an almost optimal Huffman tree with optimal time and work. This also leads to the first parallel algorithm that constructs exact Huffman codes with maximum codeword length H in time O(H) with n/logn processors, if the elements are sorted.     

Fast and Stable Reduction of Diagonal Plus Semi-Separable Matrices to Tridiagonal and Bidiagonal Form

A two-way chasing algorithm to reduce a diagonal plus a symmetric semi-separable matrix to a symmetric tridiagonal one and an algorithm to reduce a diagonal plus an unsymmetric semi-separable matrix to a bidiagonal one are considered. Both algorithms are fast and stable, requiring a computational cost of N ², where N is the order of the considered matrix.