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In this paper, we study the problem of vector scheduling with rejection on two identical parallel machines, where the objective is to minimize the sum of maximum load over all dimensions and machines and the total penalty cost. We present a 3-approximation algorithm and a 2.54-approximation algorithm based randomized rounding for the general case. When the number of dimensions is fixed, we design a fully polynomial time approximation scheme based on dynamic programming. Finally, we design an online algorithm with competitive ratio 1.62d, where d is the number of dimensions. [ABSTRACT FROM AUTHOR]

Second-order backward difference formula (BDF2) is considered for time approximation of Riesz space-fractional diffusion equations. The Riesz space derivative is approximated by the second-order fractional centre difference formula. To improve the computational efficiency, an alternating directional implicit scheme is also proposed for solving two-dimensional space-fractional diffusion problems. Numerical experiments are provided to verify our theory and to show the effectiveness of numerical algorithms. [ABSTRACT FROM AUTHOR]

We introduce a new iteration algorithm for solving the Ky Fan inequality over the fixed point set of a nonexpansive mapping, where the cost bifunction is monotone without Lipschitz-type continuity. The algorithm is based on the idea of the ergodic iteration method for solving multi-valued variational inequality which is proposed by Bruck [On the weak convergence of an ergodic iteration for the solution of variational inequalities for monotone operators in Hilbert space, J. Math. Anal. Appl. 61 (1977), pp. 159–164] and the auxiliary problem principle for equilibrium problems P.N. Anh, T.N. Hai, and P.M. Tuan. [On ergodic algorithms for equilibrium problems, J. Glob. Optim. 64 (2016), pp. 179–195]. By choosing suitable regularization parameters, we also present the convergence analysis in detail for the algorithm and give some illustrative examples. [ABSTRACT FROM PUBLISHER]

In this paper, an approximation of the optimal compressor function using the quadratic spline functions with 2L = 8 segments is described. Since the quadratic spline with 2L = 8 segments provides better approximation of the optimal compression function than quadratic spline with 2L = 4 segments, capitalizing on the benefits of the obtained spline approximation, quantizer designing process is firstly performed for the so assumed number of segments and the Laplacian source of a unit variance. Then, to enhance the usability of the proposed model, the switched quantization technique is applied and a beneficial analysis is derived, providing insight in the robustness of the proposed quantizer performances with respect to the mismatch in designed for and applied to variances. Reached quality has been compared to another model from the literature, and it has been shown that the proposed model outperforms the previous model by almost 1.3 dB. [ABSTRACT FROM PUBLISHER]

We consider the initial boundary value problem of the long-short wave equations on the whole line. A fully discrete spectral approximation scheme is developed based on Chebyshev rational functions in space and central difference in time. A priori estimates are derived which are crucial to study numerical stability and convergence of the fully discrete scheme. Then, unconditional numerical stability is proved. Convergence of the fully discrete scheme is shown by the method of error estimates. Finally, numerical experiments are presented to demonstrate the efficiency and accuracy of the convergence results. [ABSTRACT FROM PUBLISHER]

The capacitated unit covering problem is a generalization of the bin packing and the unit covering problems. In its one-dimensional case, there arenweighted points on a line and we want to partition them into a minimum number of sets such that (i) the total weight of points in each set is no more than one and (ii) the points in each set can be covered by a unit-length interval. The problem is not approximable within a factor better than 1.5 unless P = NP. We analyse a generalization of the first-fit algorithm for this problem, which runs inO(nlogn) time, and prove that when no point has weight more than, its approximation ratio is exactly ≈ 1.667. [ABSTRACT FROM AUTHOR]

A lot of heuristic algorithms, such as Evolutionary algorithms (EAs), are used to solve the maximum leaf spanning tree (MLST) problem which is non-deterministic polynomial time hard (NP-hard). However, the performance analysis of EAs on the MLST problem has seldom been studied theoretically. In this paper, we theoretically analyze the performance of the (1+1) EA on the MLST problem. We demonstrate that the (1+1) EA obtains-approximation ratio and 3-approximation ratio on this problem in expected polynomial runtimeO(nm2) andO(nm4), respectively, wherenis the number of nodes andmis the number of edges in a connected undirected graph. Furthermore, we reveal that the (1+1) EA can outperform the local search algorithms on two instances of the MLST problem. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a computational study on scaling techniques in gradient projection-type (GP-type) methods for deblurring of astronomical images corrupted by Poisson noise. In this case, the imaging problem is formulated as a non-negatively constrained minimization problem in which the objective function is the sum of a fit-to-data term, the Kullback–Leibler divergence, and a Tikhonov regularization term. The considered GP-type methods are formulated by a common iteration formula, where the scaling matrix and the step-length parameter characterize the different algorithms. Within this formulation, both first-order and Newton-like methods are analysed, with particular attention to those implementation features and behaviours relevant for the image restoration problem. The numerical experiments show that suited scaling strategies can enable the GP methods to quickly approximate accurate reconstructions and then are useful for designing effective image deblurring algorithms. [ABSTRACT FROM PUBLISHER]

Variational image restoration models for both additive and multiplicative noise (MN) removal are rarely encountered in the literature. This paper proposes a new variational model and a fast algorithm for its numerical approximation to remove independent additive and MN from digital images. Two previous works by L. Rudin, S. Osher, and E. Fatemi [Nonlinear total variation based noise removal algorithms, Phys. D 60 (1992), pp. 259–268] and Z. Jin and X. Yang [Analysis of a new variational model for multiplicative noise removal, J. Math. Anal. Appl. 362 (2010), pp. 415–426] are used to develop the new model. As a result, developing a fast numerical algorithm is difficult because the associated Euler–Lagrange equation is highly nonlinear and standard unilevel iterative methods are not appropriate. To this end, we develop an efficient nonlinear multigrid approach via a robust fixed-point smoother. Numerical tests using both synthetic and realistic images not only confirm that our new model delivers quality results but also that the proposed numerical algorithm allows a very fast numerical realization of the model. [ABSTRACT FROM PUBLISHER]

In this article we present a third-order family of methods for solving nonlinear equations. Some well-known methods belong to our family, for example Halley's method, method (24) from [M. Basto, V. Semiao, and F.L. Calheiros, A new iterative method to compute nonlinear equations, Appl. Math. Comput. 173 (2006), pp. 468-483] and the super-Halley method from [J.M. Gutierrez and M.A. Hernandez, An acceleration of Newton's method: Super-Halley method, Appl. Math. Comput. 117 (2001), pp. 223-239]. The convergence analysis shows the third order of our family. We also give sufficient conditions for the stopping inequality |xn+1-α|≤|xn+1-xn| for this family. Comparison of the family members shows that there are no significant differences between them. Several examples are presented and compared. [ABSTRACT FROM AUTHOR]

This paper develops an iterative algorithm for the solution to a variable-coefficient semilinear heat equation with nonlocal boundary conditions in the reproducing space. It is proved that the approximate sequence un(x, t) converges to the exact solution u(x, t). Moreover, the partial derivatives of un(x, t) are also convergent to the partial derivatives of u(x, t). And the approximate sequence un(x, t) is the best approximation under a complete normal orthogonal system. [ABSTRACT FROM AUTHOR]

Given a translating and rotating rod robot in a plane in the presence of polygonal obstacles with the initial and final placements of the rod known, the d 1 -optimal motion planning problem is defined as finding a collision-free motion of the rod such that the orbit length of a fixed but arbitrary point F on the rod is minimized. In this paper we study a special case of this problem in which the rod can translate freely, but can only rotate by some pre-specified given angles around F . We first characterize the d 1 -optimal motion of the robot under the given conditions and then present a (1 + ε)–approximation algorithm for finding the optimal path. The running time of the algorithm is bounded by a polynomial in terms of some parameters related to the problem input. [ABSTRACT FROM AUTHOR]