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Highlights: [•] Aiming at the problem that how to classify T-splines this paper gives a mathematical analysis, and a sufficient condition of standard T-splines is also given. [•] Then this paper presents an algorithm of determining the T-spline classification, and we can get the inherently mathematical properties of T-splines by the algorithm. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we consider the problem of clustering a set of n finite point-sets in d-dimensional Euclidean space. Different from the traditional clustering problem (called points clustering problem where the to-be-clustered objects are points), the point-sets clustering problem requires that all points in a single point-set be clustered into the same cluster. This requirement disturbs the metric property of the underlying distance function among point-sets and complicates the clustering problem dramatically. In this paper, we use a number of interesting observations and techniques to overcome this difficulty. For the k-center clustering problem on point-sets, we give an -time 3-approximation algorithm and an -time -approximation algorithm, where m is the total number of input points and k is the number of clusters. When k is a small constant, the performance ratio of our algorithm reduces to for any . For the k-median problem on point-sets, we present a polynomial time -approximation algorithm. Our approaches are rather general and can be easily implemented for practical purpose. [Copyright &y& Elsevier]

In this paper we establish approximation preserving reductions between scheduling problems in which jobs either consume some raw materials, or produce some intermediate products, and variants of the knapsack problem. Through the reductions, we get new approximation algorithms, as well as inapproximability results for the scheduling problems. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we discuss constrained approximation with arbitrary-level hanging nodes in adaptive higher-order finite element methods ( -FEM) for three-dimensional problems. This technique enables using highly irregular meshes, and it greatly simplifies the design of adaptive algorithms as it prevents refinements from propagating recursively through the finite element mesh. The technique makes it possible to design efficient adaptive algorithms for purely hexahedral meshes. We present a detailed mathematical description of the method and illustrate it with numerical examples. [Copyright &y& Elsevier]

Abstract: Let and be nontrivial involutions, i.e., and . A matrix is called -symmetric if . This paper presents a -symmetric matrix solution to the inverse eigenproblem with a leading principal submatrix constraint. The solvability condition of the constrained inverse eigenproblem is also derived. The existence, the uniqueness and the expression of the -symmetric matrix solution to the best approximation problem of the constrained inverse eigenproblem are achieved, respectively. An algorithm is presented to compute the -symmetric matrix solution to the best approximation problem. Two numerical examples are given to illustrate the effectiveness of our results. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the problem of computing a minimum bending energy path (or MinBEP) in a simple corridor. Given a simple 2D corridor C bounded by straight line segments and arcs of radius 2r, the MinBEP problem is to compute a path P inside C and crossing two pre-specified points s and t located at each end of C so that the bending energy of P is minimized. For this problem, we first show how to lower bound the bending energy of an optimal curve with bounded curvature, and then use this lower bound to design a -approximation algorithm for this restricted version of the MinBEP problem. Our algorithm is based on a number of interesting geometric observations and approximation techniques on smooth curves, and can be easily implemented for practical purpose. It is the first algorithm with a guaranteed performance ratio for the MinBEP problem. [Copyright &y& Elsevier]

Abstract: This paper introduces new and significantly fast algorithms to evaluate the price of double barrier options using binomial trees. To compute the price of double barrier options accurately, trees with large numbers of steps must be used, which is time consuming. In order to overcome this weakness, we develop new computational algorithms based on the spectral expansion method. The original idea of this method is coming from the eigenexpansion approach in PDEs. We show that this method enables us to compute double barrier options within 0.07 s, even if we use binomial trees with one billion steps. Moreover, this algorithm is easy to implement. In addition, the prices obtained by the proposed approach are always the same as those obtained by conventional binomial trees and show a good approximation to those by earlier studies. [Copyright &y& Elsevier]

Abstract: A semi-linear elliptic problem with variable coefficient is approximated by expanded mixed formulation based on the RTN and BDM mixed finite elements. In order to solve the nonlinear approximation system of equations efficiently, a two-grid algorithm is considered and discussed in this paper. The work includes a small nonlinear system on a coarse grid space with mesh size and a linear system on a fine grid space with mesh size . It follows from error estimates that asymptotically optimal accuracy can be obtained as long as the mesh sizes satisfy in the norm. Some numerical examples are presented to illustrate the theoretical results. [Copyright &y& Elsevier]

Abstract: In this paper, a new definition of a reduced Padé approximant and an algorithm for its computation are proposed. Our approach is based on the investigation of the kernel structure of the Toeplitz matrix. It is shown that the reduced Padé approximant always has nice properties which the classical Padé approximant possesses only in the normal case. The new algorithm allows us to avoid the appearance of Froissart doublets induced by computer roundoff in the non-normal Padé table. [Copyright &y& Elsevier]

Abstract: In this paper we introduce a new boundary condition that can be used when reconstructing an image from observed blurred and noisy data. Our approach uses information from the observed image to enforce boundary conditions that continue image features such as edges and texture across the boundary. Because of its similarity to methods used in texture synthesis, we call our approach synthetic boundary conditions. We provide an efficient algorithm for implementing the new boundary condition, and provide a linear algebraic framework for the approach that puts it in the context of more classical and well known image boundary conditions, including zero, periodic, reflective, and anti-reflective. Extensive numerical experiments show that our new synthetic boundary conditions provide a more accurate approximation of the true image scene outside the image boundary, and thus allow for better reconstructions of the unknown, true image scene. [Copyright &y& Elsevier]

Abstract: Symmetric rank-one (SR1) is one of the competitive formulas among the quasi-Newton (QN) methods. In this paper, we propose some modified SR1 updates based on the modified secant equations, which use both gradient and function information. Furthermore, to avoid the loss of positive definiteness and zero denominators of the new SR1 updates, we apply a restart procedure to this update. Three new algorithms are given to improve the Hessian approximation with modified secant equations for the SR1 method. Numerical results show that the proposed algorithms are very encouraging and the advantage of the proposed algorithms over the standard SR1 and BFGS updates is clearly observed. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we present a new algorithm to solve general linear fifth-order boundary value problems (BVPs) in the reproducing kernel space . Representation of the exact solution is given in the reproducing kernel space. Its approximate solution is obtained by truncating the -term of the exact solution. Some examples are displayed to demonstrate the computational efficiency of the method. [Copyright &y& Elsevier]

Abstract: Borodin, Nielsen and Rackoff  introduced the class of priority algorithms as a framework for modeling deterministic greedy-like algorithms. In this paper we address the effect of randomization in greedy-like algorithms. More specifically, we consider approximation ratios within the context of randomized priority algorithms. As case studies, we prove inapproximation results for two well-studied optimization problems, namely facility location and makespan scheduling. [Copyright &y& Elsevier]

Abstract: Many real problems can be modeled to the problems with a hierarchical structure, and bilevel programming is a useful tool to solve the hierarchical optimization problems. So the bilevel programming is widely applied, and numerous methods have been proposed to solve this programming. In this paper, we propose an approximate programming algorithm to solve bilevel nonlinear programming problem. Finally, the example illustrates the feasibility of the proposed algorithm. [Copyright &y& Elsevier]

Abstract: Let be a simple graph without isolated vertices. A vertex set is a paired-dominating set if every vertex in has a neighbor in and the induced subgraph has a perfect matching. In this paper, we investigate the approximation hardness of paired-domination in graphs. For weighted paired-domination, an approximation algorithm in general graphs and an exact dynamic programming style algorithm in trees are also given. [Copyright &y& Elsevier]

Abstract: By introducing a bivariate matrix-valued linear functional on the scalar polynomial space, a general two-dimensional (2-D) matrix Padé-type approximant () in the inner product space is defined in this paper. The coefficients of its denominator polynomials are determined by taking the direct inner product of matrices. The remainder formula is developed and an algorithm for the numerator polynomials is presented when the generating polynomials are given in advance. By means of the Hankel-like coefficient matrix, a determinantal expression of is presented. Moreover, to avoid the computation of the determinants, two efficient recursive algorithms are proposed. At the end the method of is applied to partial realization problems of 2-D linear systems. [Copyright &y& Elsevier]

Abstract: In this paper, we present a new algorithm for computing local extrema by modifying and combining algorithms in symbolic and numerical computation. This new algorithm improves the classical steepest descent method that may not terminate, by combining a Sturm’s theorem based separation method and a sufficient condition on infeasibility. In addition, we incorporate a grid subdivision method into our algorithm to approximate all local extrema. The complexity of our algorithm is polynomial in a newly defined condition number, and singly exponential in the number of variables. [Copyright &y& Elsevier]

Abstract: This paper deals with the maximum triangle packing problem. For this problem, Hassin and Rubinstein gave a randomized polynomial-time approximation algorithm that achieves an expected ratio of for any constant . By modifying their algorithm, we obtain a new randomized polynomial-time approximation algorithm for the problem which achieves an expected ratio of for any constant . [Copyright &y& Elsevier]

Abstract: For a fixed family of graphs, an -packing in a graph is a set of pairwise vertex-disjoint subgraphs of , each isomorphic to an element of . Finding an -packing that maximizes the number of covered edges is a natural generalization of the maximum matching problem, which is just . In this paper we provide new approximation algorithms and hardness results for the -packing problem where . We show that already for the -packing problem is APX-complete, and, in fact, we show that it remains so even for graphs with maximum degree 4. On the positive side, we give an approximation algorithm with approximation ratio at most 2 for every fixed . For we obtain better approximations. For we obtain a simple -approximation, achieving a known ratio that follows from a more involved algorithm of Halldórsson. For , we obtain a -approximation, and for we obtain a -approximation. [Copyright &y& Elsevier]

We present a 0.7499-approximation algorithm for Max Set Splitting in this paper. The previously best known result for this problem is a 0.7240-approximation by Andersson and Engebretsen (Inform. Process. Lett. 65 (1998) 305), which is based on a semidefinite programming (SDP) relaxation. Our improvement is resulted from a strengthened SDP relaxation, an improved rounding method, and a tighter analysis compared with that in Andersson and Engebretsen (1998). [Copyright &y& Elsevier]