On finding representative non-dominated points for bi-objective integer network flow problems

This paper proposes a new algorithm to find a representation of the set of all non-dominated points of the bi-objective integer network flow problem. The algorithm solves a sequence of ε-constraint problems with a branch-and-bound algorithm to find a subset of non-dominated points that represents the set of all non-dominated points well in the sense of coverage or uniformity. At each iteration of the algorithm, one non-dominated point, determined by solving one ε-constraint problem, is added to the representation until it is guaranteed that the representation has the desired quality. Computational experiments on different problem types show the efficacy of the algorithm.     

A linear time algorithm for max-min length triangulation of a convex polygon

We consider the following planar max-min length triangulation problem: given a set of n points in the Euclidean plane, find a triangulation such that the length of the shortest edge in the triangulation is maximized. In this paper, a linear time algorithm is proposed for computing the max-min length triangulation of a set of points in convex position. In addition, an O(nlogn) time algorithm is proposed for computing the max-min length k-set triangulation of a set of points in convex position, where we are to compute a set of k vertices such that the max-min length triangulation on them is minimized over all possible k-set. We further show that the graph version of max-min length triangulation is NP-complete, and some common heuristics such as greedy algorithm are in general not able to give a bounded-ratio approximation to the max-min length triangulation.     

Finding extreme supported solutions of biobjective network flow problems: An enhanced parametric programming approach

We address the problem of determining a complete set of extreme supported efficient solutions of biobjective minimum cost flow (BMCF) problems. A novel method improving the classical parametric method for this biobjective problem is proposed. The algorithm runs in O(Nn(m + nlogn)) time determining all extreme supported non-dominated points in the outcome space and one extreme supported efficient solution associated with each one of them. Here n is the number of nodes, m is the number of arcs and N is the number of extreme supported non-dominated points in outcome space for the BMCF problem. The memory space required by the algorithm is O(n + m) when the extreme supported efficient solutions are not required to be stored in RAM. Otherwise, the algorithm requires O(N + m) space. Extensive computational experiments comparing the performance of the proposed method and a standard parametric network simplex method are presented.     

Computing all efficient solutions of the biobjective minimum spanning tree problem

A common way of computing all efficient (Pareto optimal) solutions for a biobjective combinatorial optimisation problem is to compute first the extreme efficient solutions and then the remaining, non-extreme solutions. The second phase, the computation of non-extreme solutions, can be based on a “k-best” algorithm for the single-objective version of the problem or on the branch-and-bound method. A k-best algorithm computes the k-best solutions in order of their objective values. We compare the performance of these two approaches applied to the biobjective minimum spanning tree problem. Our extensive computational experiments indicate the overwhelming superiority of the k-best approach. We propose heuristic enhancements to this approach which further improve its performance.     

Power-aware scheduling for makespan and flow

We consider offline scheduling algorithms that incorporate speed scaling to address the bicriteria problem of minimizing energy consumption and a scheduling metric. For makespan, we give a linear-time algorithm to compute all non-dominated solutions for the general uniprocessor problem and a fast arbitrarily-good approximation for multiprocessor problems when every job requires the same amount of work. We also show that the multiprocessor problem becomes NP-hard when jobs can require different amounts of work. For total flow, we show that the optimal flow corresponding to a particular energy budget cannot be exactly computed on a machine supporting exact real arithmetic, including the extraction of roots. This hardness result holds even when scheduling equal-work jobs on a uniprocessor. We do, however, extend previous work by Pruhs et al. to give an arbitrarily-good approximation for scheduling equal-work jobs on a multiprocessor.     

On the K best integer network flows

We address the problem of finding the K best integer solutions of a linear integer network flow problem. We design an O(f(n,m,L,U)+KmS(n,m,L)) time and O(K+m) memory space algorithm to determine the K best integer solutions, in a directed network with n nodes, m arcs, maximum absolute value cost L, and an upper bound U on arc capacities and node supplies. f(n,m,L,U) is the best time needed to solve the minimum cost flow problem in a directed network and S(n,m,L) is the best time to solve the single-source shortest path problem in a network with non-negative lengths. The introduced algorithm efficiently determines a “proper minimal cycle” by taking advantage of the relationship between the best solutions. This way, we improve the theoretical as well as practical memory space bounds of the well-known method due to Hamacher. Our computational experiments confirm this result.     

Fast modified global k-means algorithm for incremental cluster construction

The k-means algorithm and its variations are known to be fast clustering algorithms. However, they are sensitive to the choice of starting points and are inefficient for solving clustering problems in large datasets. Recently, incremental approaches have been developed to resolve difficulties with the choice of starting points. The global k-means and the modified global k-means algorithms are based on such an approach. They iteratively add one cluster center at a time. Numerical experiments show that these algorithms considerably improve the k-means algorithm. However, they require storing the whole affinity matrix or computing this matrix at each iteration. This makes both algorithms time consuming and memory demanding for clustering even moderately large datasets. In this paper, a new version of the modified global k-means algorithm is proposed. We introduce an auxiliary cluster function to generate a set of starting points lying in different parts of the dataset. We exploit information gathered in previous iterations of the incremental algorithm to eliminate the need of computing or storing the whole affinity matrix and thereby to reduce computational effort and memory usage. Results of numerical experiments on six standard datasets demonstrate that the new algorithm is more efficient than the global and the modified global k-means algorithms.     

Gradient Based Image Motion Estimation Without Computing Gradients

Computing an optical flow field using the classical image motion constraint equation is difficult owing to the aperture problem and the need to compute the image intensity derivatives via numerical differentiation—an extremely unstable operation. We integrate the above constraint equation over a significant spatio-temporal support and use Gauss's Divergence theorem to replace the volume integrals by surface integrals, thereby eliminating the intensity derivatives and numerical differentiation. We tackle the aperture problem by fitting an affine flow field model to a small space-time window. Using this affine model our new integral motion constraint approach leads to a robust and accurate algorithm to compute the optical flow field. Extensive experimentation confirms that the algorithm is indeed robust and accurate.     

Uncertain Voronoi diagram

In this paper, we introduce the fuzzy Voronoi diagram as an extension of the Voronoi diagram. We assume Voronoi sites to be fuzzy points and then define the Voronoi diagram for this kind of sites, then we provide an algorithm for computing this diagram based on Fortune's algorithm which costs O(nlogn) time. Also we introduce the fuzzy Voronoi diagram for a set of fuzzy circles, rather than fuzzy points, of the same radius. We prove that the boundary of this diagram is formed by the intersection of some hyperbolae, and finally we provide an O(n³logn)-time algorithm to compute the boundary.     

A direct numerical simulation of axisymmetric cryogenic two-phase flows in a pipe with phase change

An accurate finite-volume based numerical method for the simulation of a cryogenic two-phase flow with phase change heat transfer, consisting of a saturated liquid slug translating in its own superheated vapor in a circular pipe is presented. This method is built on a sharp interface concept and developed on an Eulerian Cartesian fixed-grid with a cut-cell scheme and marker points to track the moving interface. The unsteady, axisymmetric Navier–Stokes equations in both liquid and vapor phases are solved separately. The mass continuity, momentum flux conditions and conservation of energy are explicitly matched at the true boundary between the two phases to determine the interface shape and movement. A quadratic curve fitting algorithm with marker points is used to yield smooth and accurate information of the interface curvatures.It is uniquely demonstrated for the first time with the current method that conservation of mass is strictly enforced for continuous infusion of flow into the domain of computation. The method has been used to compute the velocity, pressure and temperature fields and the deformation of the liquid core. It is also shown that the current method is capable of producing accurate results for a wide range of Reynolds number, Re, Weber number, We, Jakob number, Ja and large property jumps at the interface.     

A saturation method for the modal μ-calculus over pushdown systems

We present an algorithm for computing directly the denotation of a μ-calculus formula χ over the configuration graph of a pushdown system. Our method gives the first extension of the saturation technique to the full μ-calculus. Finite word automata are used to represent sets of pushdown configurations. Starting from an initial automaton, we perform a series of automaton manipulations which compute the denotation by recursion over the structure of the formula. We introduce notions of under-approximation (soundness) and over-approximation (completeness) that apply to automaton transitions rather than runs. Our algorithm is relatively simple and direct, and avoids an immediate exponential blow up. Finally, we show experimentally that the direct algorithm is more efficient than via a reduction to parity games.     

Manifold splines with a single extraordinary point

This paper develops a novel computational technique to define and construct manifold splines with only one singular point by employing the rigorous mathematical theory of Ricci flow. The central idea and new computational paradigm of manifold splines are to systematically extend the algorithmic pipeline of spline surface construction from any planar domain to an arbitrary topology. As a result, manifold splines can unify planar spline representations as their special cases. Despite its earlier success, the existing manifold spline framework is plagued by the topology-dependent, large number of singular points (i.e., |2g−2| for any genus-g surface), where the analysis of surface behaviors such as continuity remains extremely difficult. The unique theoretical contribution of this paper is that we devise new mathematical tools so that manifold splines can now be constructed with only one singular point, reaching their theoretic lower bound of singularity for real-world applications. Our new algorithm is founded upon the concept of discrete Ricci flow and associated techniques. First, Ricci flow is employed to compute a special metric of any manifold domain (serving as a parametric domain for manifold splines), such that the metric becomes flat everywhere except at one point. Then, the metric naturally induces an affine atlas covering the entire manifold except this singular point. Finally, manifold splines are defined over this affine atlas. The Ricci flow method is theoretically sound, and practically simple and efficient. We conduct various shape experiments and our new theoretical and algorithmic results alleviate the modeling difficulty of manifold splines, and hence, promote the widespread use of manifold splines in surface and solid modeling, geometric design, and reverse engineering.     

求解多目标流水车间调度Pareto最优解的遗传强化算法

针对多目标流水车间调度Pareto最优问题, 本文建立了以最大完工时间和最大拖延时间为优化目标的多目标流水车间调度问题模型, 并设计了一种基于Q-learning的遗传强化学习算法求解该问题的Pareto最优解. 该算法引入状态变量和动作变量, 通过Q-learning算法获得初始种群, 以提高初始解质量. 在算法进化过程中, 利用Q表指导变异操作, 扩大局部搜索范围. 采用Pareto快速非支配排序以及拥挤度计算提高解的质量以及多样性, 逐步获得Pareto最优解. 通过与遗传算法、NSGA-II算法和Q-learning算法进行对比实验, 验证了改进后的遗传强化算法在求解多目标流水车间调度问题Pareto最优解的有效性.     

A Dijkstra-like method computing all extreme supported non-dominated solutions of the biobjective shortest path problem

We address the problem of determining all extreme supported solutions of the biobjective shortest path problem. A novel Dijkstra-like method generalizing Dijkstra׳s algorithm to this biobjective case is proposed. The algorithm runs in O(N(m+n log n)) time to solve one-to-one and one-to-all biobjective shortest path problems determining all extreme supported non-dominated points in the outcome space and one supported efficient path associated with each one of them. Here n is the number of nodes, m is the number of arcs and N is the number of extreme supported points in outcome space for the one-to-all biobjective shortest path problem. The memory space required by the algorithm is O(n+m) for the one-to-one problem and O(N+m) for the one-to-all problem. A computational experiment comparing the performance of the proposed methods and state-of-the-art methods is included.     

Capturing crossings: Convex hulls of segment and plane intersections

We give a simple O(nlogn) algorithm to compute the convex hull of the (possibly Θ(n²)) intersection points in an arrangement of n line segments in the plane. We also show an arrangement of dn hyperplanes in d-dimensions whose arrangement has Θ(nd−1) intersection points on the convex hull.     

自适应的非支配排序遗传算法

针对带精英策略的非支配排序遗传算法不能根据环境变化自适应地动态调整运行参数,难以实现对解空间的高效搜索,提出一种自适应的非支配排序遗传算法.所提出算法根据运行阶段、运行代数和当前临时种群非支配个体数动态调整进化个体的运行参数,通过提高进化算子的自适应能力使算法具有自适应性.经实验对比,所提出算法在收敛性、多样性两方面确有提升,可以有效提高原算法的搜索能力.     

Drawing layered graphs with port constraints

Complex software systems are often modeled using data flow diagrams, in which nodes are connected to each other through dedicated connection points called ports. The influence a layout algorithm has on the placement of ports is determined by port constraints defined on the corresponding node.In this paper we present approaches for integrating port constraints into the layer-based approach to graph drawing pioneered by Sugiyama et al. We show how our layout algorithm, called KLay Layered, progresses from relaxed to more restricted port constraint levels as it executes, and how established algorithms for crossing minimization and edge routing can be extended to support port constraints. Compared to the previous layout algorithms supporting ports, our algorithm produces fewer edge crossings and bends and yields pleasing results.We also explain and evaluate how layout algorithms can be kept simple by using the concept of intermediate processors to structure them in a modular way. A case study integrating our layout algorithm into UC Berkeley's Ptolemy tool illustrates how KLay Layered can be integrated into Java-based applications.     

一种基于光流的障碍物估计算法

移动机器人在行进过程中必须能够检测和躲避障碍物,文章提出了一种使用光流场估计障碍物区域的算法。使用结合从粗到精策略的最小加权二乘法的方法计算光流,从而估计图像序列中可能的障碍物位置,为后续的接近时间计算提供了良好的基础。大量实地实验验证了该方法的有效性和可行性。     

Computing efficiently the lattice width in any dimension

We provide an algorithm for the exact computation of the lattice width of a set of points K in Z² in linear-time with respect to the size of K. This method consists in computing a particular surrounding polygon. From this polygon, we deduce a set of candidate vectors allowing the computation of the lattice width. Moreover, we describe how this new algorithm can be extended to an arbitrary dimension thanks to a greedy and practical approach to compute a surrounding polytope. Indeed, this last computation is very efficient in practice as it processes only a few linear time iterations whatever the size of the set of points. Hence, it avoids complex geometric processings.     

Capacity-Constrained Delaunay Triangulation for point distributions

Sample point distributions possessing blue noise spectral characteristics play a central role in computer graphics, but are notoriously difficult to generate. We describe an algorithm to very efficiently generate these distributions. The core idea behind our method is to compute a Capacity-Constrained Delaunay Triangulation (CCDT), namely, given a simple polygon P in the plane, and the desired number of points n, compute a Delaunay triangulation of the interior of P with n Steiner points, whose triangles have areas which are as uniform as possible. This is computed iteratively by alternating update of the point geometry and triangulation connectivity. The vertex set of the CCDT is shown to have good blue noise characteristics, comparable in quality to those of state-of-the-art methods, achieved at a fraction of the runtime. Our CCDT method may be applied also to an arbitrary density function to produce non-uniform point distributions. These may be used to half-tone grayscale images.