一种用于求解TSP问题的随机最佳插入烟花算法

TSP问题是一个NP难问题,求解时间随问题规模呈几何级数增长,如何在较短时间内求得更精确的解一直是重要的研究问题。因为烟花算法在求解过程中能够快速收敛,而且能跳出局部最优解,所以基于烟花算法改进了爆炸资源分配的方式,创新性地提出了2个算子：抛弃节点重新插入的爆炸算子和抛弃路径重新插入的变异算子。再使用精英与轮盘赌相结合的烟花选择策略,设计了一种随机最佳插入的烟花算法（RBIFWA）。将该算法与基本烟花算法、混沌烟花算法、离散蝙蝠算法和自适应模拟退火蚁群算法进行比较,结果显示,RBIFWA算法在迭代次数上明显优于其他算法,且算法的解更加接近已知最优解,表明RBIFWA算法在求解TSP问题上具有更加优秀的性能和更高的求解质量。     

NP-Hardness of Broadcast Scheduling and Inapproximability of Single-Source Unsplittable Min-Cost Flow

We consider the version of broadcast scheduling where a server can transmit W messages of a given set at each time-step, answering previously made requests for these messages. The goal is to minimize the average response time (ART) if the amount of requests is known in advance for each time-step and message. We prove that this problem is NP-hard, thus answering an open question stated by Kalyanasundaram, Pruhs and Velauthapillai (Proceedings of ESA 2000, LNCS 1879, 2000, pp. 290–301). Furthermore, we present an approximation algorithm that is allowed to send several messages at once. Using six channels for transmissions, the algorithm achieves an ART that is at least as good as the optimal solution using one channel. From the NP-hardness of broadcast scheduling we derive a new inapproximability result of (2 − ε, 1) for the (congestion, cost) bicriteria version of the single source unsplittable min-cost flow problem, for arbitrary ε > 0. The result holds even in the often considered case where the maximum demand is less than or equal to the minimum edge capacity (d _max ≤ u _min), a case for which an algorithm with ratio (3, 1) was presented by Skutella.     

Improved Approximation Algorithms for Maximum Resource Bin Packing and Lazy Bin Covering Problems

In this paper, we study two variants of the bin packing and covering problems called Maximum Resource Bin Packing (MRBP) and Lazy Bin Covering (LBC) problems, and present new approximation algorithms for them. For the offline MRBP problem, the previous best known approximation ratio is \frac65\frac{6}{5} (=1.2) achieved by the classical First-Fit-Increasing (FFI) algorithm (Boyar et al. in Theor. Comput. Sci. 362(1–3):127–139, 2006). In this paper, we give a new FFI-type algorithm with an approximation ratio of \frac8071\frac{80}{71} (≈1.12676). For the offline LBC problem, it has been shown in Lin et al. (COCOON, pp. 340–349, 2006) that the classical First-Fit-Decreasing (FFD) algorithm achieves an approximation ratio of \frac7160\frac{71}{60} (≈1.18333). In this paper, we present a new FFD-type algorithm with an approximation ratio of \frac1715\frac{17}{15} (≈1.13333). Our algorithms are based on a pattern-based technique and a number of other observations. They run in near linear time (i.e., O(nlog n)), and therefore are practical.     

Particle swarm optimization-based fixed-structure <Emphasis Type="Italic">ℋ</Emphasis><Subscript>∞</Subscript> control design

In this paper, a new robust fixed-structure ℋ _∞ controller design based on the Particle Swarm Optimization (PSO) technique is proposed. The optimization-based structured synthesis problem is formulated and solved by a constrained PSO algorithm. In the proposed approach, the ℋ _∞ controller’s structure is selectable. PI and PID controller structures are especially adopted. The case study of an electrical DC drive benchmark is adopted to illustrate the efficiency and viability of the proposed control approach. A comparison to another similar evolutionary algorithm, such as Genetic Algorithm Optimization (GAO), shows the superiority of the PSO-based method to solve the formulated optimization problem. Simulations and experimental results show the advantages of simple structure, lower order and robustness of the proposed controller.     

A special case of the single-machine total tardiness problem is NP-hard

In this paper, it is shown that the special case B-1 of the single-machine total tardiness problem 1 ∥ ΣT _j is NP-hard in the ordinary sense. For this case, there exists a pseudo-polynomial algorithm with run time O(n σp _j). Published in Russian in Izvestiya Akademii Nauk. Teoriya i Sistemy Upravleniya, 2006, No. 3, pp. 120–128. Article was translated by the authors.     

Iterative Stokes Solvers in the Harmonic Velte Subspace

We explore the prospects of utilizing the decomposition of the function space (H ¹ ₀) ⁿ (where n=2,3) into three orthogonal subspaces (as introduced by Velte) for the iterative solution of the Stokes problem. It is shown that Uzawa and Arrow-Hurwitz iterations – after at most two initial steps – can proceed fully in the third, smallest subspace. For both methods, we also compute optimal iteration parameters. Here, for two-dimensional problems, the lower estimate of the inf-sup constant by Horgan and Payne proves useful and provides an inclusion of the spectrum of the Schur complement operator of the Stokes problem. We further consider the conjugate gradient method in the third Velte subspace and derive a corresponding convergence estimate. Computational results show the effectiveness of this approach for discretizations which admit a discrete Velte decomposition. Received June 11, 1999; revised October 27, 2000     

Numerical Evaluation of the Accuracy and Stability Properties of High-order Direct Stokes Solvers with or without Temporal Splitting

The temporal stability and effective order of two different direct high-order Stokes solvers are examined. Both solvers start from the primitive variables formulation of the Stokes problem, but are distinct by the numerical uncoupling they apply on the Stokes operator. One of these solvers introduces an intermediate divergence free velocity for performing a temporal splitting (J. Comput. Phys. [1991] 97, 414–443) while the other treats the whole Stokes problem through the evaluation of a divergence free acceleration field (C.R. Acad. Sci. Paris [1994] 319 Serie I, 1455–1461; SIAM J. Scient. Comput. [2000] 22(4), 1386–1410). The second uncoupling is known to be consistent with the harmonicity of the pressure field (SIAM J. Scient. Comput. [2000] 22(4), 1386–1410). Both solvers proceed by two steps, a pressure evaluation based on an extrapolated in time (of theoretical order J_e) Neumann condition, and a time implicit (of theoretical order J_i) diffusion step for the final velocity. These solvers are implemented with a Chebyshev mono-domain and a Legendre spectral element collocation schemes. The numerical stability of these four options is investigated for the sixteen combinations of (J_e,J_i), 1 ≤ J_e, J_i ≤ 4.     

r-Algorithms and ellipsoids

Conclusion Transformation (6) smoothing thef(x) level lines explains the effectiveness ofr(α)-algorithms from visual geometrical considerations. It may be regarded as a satisfactory interpretation of space dilation in the direction of the difference of two successive subgradients. On the other hand, it preserves the gradient flavor of the method, in contrast to the classical ellipsoid method [11, 12], which is a successful interpretation of the subgradient method with space dilation in the direction of the subgradient. A sensible combination of ellipsoids of a special kind [5] with the ellipsoids ell(x₀,a, b, c) is quite capable of producing, on the basis of a one-dimensional space dilation operator, effective algorithms that solve a broader class of problems than convex programming problems, e.g., the problem to find saddle points of convex-concave functions, particular cases of the problem of solving variational inequalities, and also special classes of linear and nonlinear complementarity problems. Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 113–134, January–February, 1996.     

Numerical Study of a Modified Time-Stepping θ-Scheme for Incompressible Flow Simulations

In [Turek (1996). Int. J. Numer. Meth. Fluids 22, 987–1011], we had performed numerical comparisons for different time stepping schemes for the incompressible Navier–Stokes equations. In this paper, we present the numerical analysis in the context of the Navier–Stokes equations for a modified time-stepping θ-scheme which has been recently proposed by Glowinski [Glowinski (2003). In: Ciarlet, P. G., and Lions, J. L. (eds.), Handbook of Numerical Analysis, Vol. IX, North-Holland, Amsterdam, pp. 3–1176]. Like the well-known classical Fractional-Step-θ-scheme which had been introduced by Glowinski [Glowinski (1985). In Murman, E. M. and Abarbanel, S. S. (eds.), Progress and Supercomputing in Computational Fluid Dynamics, Birkh?user, Boston MA; Bristeau et al. (1987). Comput. Phys. Rep. 6, 73–187], too, and which is still one of the most popular time stepping schemes, with or without operator splitting techniques, this new scheme consists of 3 substeps with nonequidistant substepping to build one macro time step. However, in contrast to the Fractional-Step-θ-scheme, the second substep can be formulated as an extrapolation step for previously computed data only, and the two remaining substeps look like a Backward Euler step so that no expensive operator evaluations for the right hand side vector with older solutions, as for instance in the Crank–Nicolson scheme, have to be performed. This modified scheme is implicit, strongly A-stable and second order accurate, too, which promises some advantageous behavior, particularly in implicit CFD simulations for the nonstationary Navier–Stokes equations. Representative numerical results, based on the software package FEATFLOW [Turek (2000). FEATFLOW Finite element software for the incompressible Navier–Stokes equations: User Manual, Release 1.2, University of Dortmund] are obtained for typical flow problems with benchmark character which provide a fair rating of the solution schemes, particularly in long time simulations.Dedicated to David Gottlieb on the occasion of his 60th anniversary     

Image Compression and Reconstruction Using pi<Subscript><Emphasis Type="Italic">t</Emphasis></Subscript>-Sigma Neural Networks

A high-order feedforward neural architecture, called pi _t -sigma (π _t σ) neural network, is proposed for lossy digital image compression and reconstruction problems. The π _t σ network architecture is composed of an input layer, a single hidden layer, and an output layer. The hidden layer is composed of classical additive neurons, whereas the output layer is composed of translated multiplicative neurons (π _t -neurons). A two-stage learning algorithm is proposed to adjust the parameters of the π _t σ network: first, a genetic algorithm (GA) is used to avoid premature convergence to poor local minima; in the second stage, a conjugate gradient method is used to fine-tune the solution found by GA. Experiments using the Standard Image Database and infrared satellite images show that the proposed π _t σ network performs better than classical multilayer perceptron, improving the reconstruction precision (measured by the mean squared error) in about 56%, on average.     

Resource scheduling with variable requirements over time

The problem of scheduling resources for tasks with variable requirements over time can be stated as follows. We are given two sequences of vectors A=A ₁,…,A _n and R=R ₁,…,R _m . Sequence A represents resource availability during n time intervals, where each vector A _i has q elements. Sequence R represents resource requirements of a task during m intervals, where each vector R _i has q elements. We wish to find the earliest time interval i, termed latency, such that for 1≤k≤m, 1≤j≤q: A _i+k−1 ^j ≥R _k ^j , where A _i+k−1 ^j and R _k ^j are the jth elements of vectors A _i+k−1 and R _k , respectively. One application of this problem is I/O scheduling for multimedia presentations. The fastest known algorithm to compute the optimal solution of this problem has computation time (Amir and Farach, in Proceedings of the ACM-SIAM symposium on discrete algorithms (SODA), San Francisco, CA, pp. 212–223, 1991; Inf. Comput. 118(1):1–11, 1995). We propose a technique that approximates the optimal solution in linear time: . We evaluated the performance of our algorithm when used for multimedia I/O scheduling. Our results show that 95% of the time, our solution is within 5% of the optimal.     

Newton Iterative Parallel Finite Element Algorithm for the Steady Navier-Stokes Equations

A combination method of the Newton iteration and parallel finite element algorithm is applied for solving the steady Navier-Stokes equations under the strong uniqueness condition. This algorithm is motivated by applying the Newton iterations of m times for a nonlinear problem on a coarse grid in domain Ω and computing a linear problem on a fine grid in some subdomains Ω _j ⊂Ω with j=1,…,M in a parallel environment. Then, the error estimation of the Newton iterative parallel finite element solution to the solution of the steady Navier-Stokes equations is analyzed for the large m and small H and h≪H. Finally, some numerical tests are made to demonstrate the the effectiveness of this algorithm.     

On the regularization of vector integer quadratic programming problems

For a vector integer quadratic programming problem, a regularizing operator is proposed that acts on a vector criterion and transforms a possibly unstable initial problem into a series of perturbed stable problems with the same Pareto set. The technique of ε-regularization is developed that allows replacing the considered problem by perturbed ε-stable problems. Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 128–134, March–April 2009.     

A Nonoverlapping Domain Decomposition Method for Legendre Spectral Collocation Problems

We consider the Dirichlet boundary value problem for Poisson’s equation in an L-shaped region or a rectangle with a cross-point. In both cases, we approximate the Dirichlet problem using Legendre spectral collocation, that is, polynomial collocation at the Legendre–Gauss nodes. The L-shaped region is partitioned into three nonoverlapping rectangular subregions with two interfaces and the rectangle with the cross-point is partitioned into four rectangular subregions with four interfaces. In each rectangular subregion, the approximate solution is a polynomial tensor product that satisfies Poisson’s equation at the collocation points. The approximate solution is continuous on the entire domain and its normal derivatives are continuous at the collocation points on the interfaces, but continuity of the normal derivatives across the interfaces is not guaranteed. At the cross point, we require continuity of the normal derivative in the vertical direction. The solution of the collocation problem is first reduced to finding the approximate solution on the interfaces. The discrete Steklov–Poincaré operator corresponding to the interfaces is self-adjoint and positive definite with respect to the discrete inner product associated with the collocation points on the interfaces. The approximate solution on the interfaces is computed using the preconditioned conjugate gradient method. A preconditioner is obtained from the discrete Steklov–Poincaré operators corresponding to pairs of the adjacent rectangular subregions. Once the solution of the discrete Steklov–Poincaré equation is obtained, the collocation solution in each rectangular subregion is computed using a matrix decomposition method. The total cost of the algorithm is O(N ³), where the number of unknowns is proportional to N ².      

Linear Time Algorithms for Exact Distance Transform

In 2003, Maurer et al. (IEEE Trans. Pattern Anal. Mach. Intell. 25:265–270, 2003) published a paper describing an algorithm that computes the exact distance transform in linear time (with respect to image size) for the rectangular binary images in the k-dimensional space ℝ ^k and distance measured with respect to L _p -metric for 1≤p≤∞, which includes Euclidean distance L ₂. In this paper we discuss this algorithm from theoretical and practical points of view. On the practical side, we concentrate on its Euclidean distance version, discuss the possible ways of implementing it as signed distance transform, and experimentally compare implemented algorithms. We also describe the parallelization of these algorithms and discuss the computational time savings associated with them. All these implementations will be made available as a part of the CAVASS software system developed and maintained in our group (Grevera et al. in J. Digit. Imaging 20:101–118, 2007). On the theoretical side, we prove that our version of the signed distance transform algorithm, GBDT, returns the exact value of the distance from the geometrically defined object boundary. We provide a complete proof (which was not given of Maurer et al. (IEEE Trans. Pattern Anal. Mach. Intell. 25:265–270, 2003) that all these algorithms work correctly for L _p -metric with 1<p<∞. We also point out that the precise form of the algorithm from Maurer et al. (IEEE Trans. Pattern Anal. Mach. Intell. 25:265–270, 2003) is not well defined for L ₁ and L _∞ metrics. In addition, we show that the algorithm can be used to find, in linear time, the exact value of the diameter of an object, that is, the largest possible distance between any two of its elements.     

A multiprocessor based heuristic for multi-dimensional multiple-choice knapsack problem

This paper presents a multiprocessor based heuristic algorithm for the Multi-dimensional Multiple Choice Knapsack Problem (MMKP). MMKP is a variant of the classical 0–1 knapsack problem, where items having a value and a number of resource requirements are divided into groups. Exactly one item has to be picked up from each group to achieve a maximum total value without exceeding the resource constraint of each type. MMKP has many real world applications including admission control in adaptive multimedia server system. Exact solution to this problem is NP-Hard, and hence is not feasible for real time applications like admission control. Therefore, heuristic solutions have been developed to solve the MMKP. M-HEU is one such heuristic, which solves the MMKP achieving a reasonable percentage of optimality. In this paper, we present a multiprocessor algorithm based on M-HEU, which runs in O(T/p+s(p)) time, where T is the time required by the algorithm using single processor, p is the number of processors and s(p), a function of p, is the synchronization overhead. We also present the worst-case analysis of our algorithm, the computation of the optimal number of processors as well as the lower bound of the total value that can be achieved by the heuristic.     

Eigenvalue problem for the Navier-Stokes operator in cylindrical coordinates

A fast, accurate, and robust numerical algorithm is proposed, suitable for parametric studies of incompressible fluid flow in a pipe. The new algorithm (or its fragments) can have a wider applicability, including cases when the computational domain contains a coordinate singularity along the polar axis r = 0 and when the dependence on the azimuth angle can be represented as a Fourier series, due to the physical symmetry of the problem. The constructed method enables the efficient solution of the eigenvalue problem for the linearized Navier-Stokes operator in cylindrical coordinates. The algorithm is based on a new change in the dependent variables, which makes it possible to circumvent the difficulties associated with coordinate singularities by taking into account the special behavior of analytic functions in the vicinity of the point r = 0. Despite the presence of coordinate singularities, the new algorithm ensures the spectral accuracy. The numerical solution of the linear problem of hydrodynamic stability involves the spatial discretization of the Navier-Stokes operator, its linearization about the stationary solution, and the reduction to the canonical eigenvalue problem of the type λx = Tx. Eigenvalues λ can then be calculated by the QR algorithm. An original method is proposed here for the reduction of the eigenvalue problem to its canonical form, employing the influence matrix technique. This method is economical and is characterized by its low sensitivity to round-off errors.     

The Deutsch–Jozsa problem: de-quantisation and entanglement

The Deutsch–Jozsa problem is one of the most basic ways to demonstrate the power of quantum computation. Consider a Boolean function f : {0, 1} ⁿ → {0, 1} and suppose we have a black-box to compute f. The Deutsch–Jozsa problem is to determine if f is constant (i.e. f(x) = const, "x ? {0,1}ⁿf(x) = \hbox {const, } \forall x \in \{0,1\}^n) or if f is balanced (i.e. f(x) = 0 for exactly half the possible input strings x ? {0,1}ⁿx \in \{0,1\}^n) using as few calls to the black-box computing f as is possible, assuming f is guaranteed to be constant or balanced. Classically it appears that this requires at least 2 ⁿ⁻¹ + 1 black-box calls in the worst case, but the well known quantum solution solves the problem with probability one in exactly one black-box call. It has been found that in some cases the algorithm can be de-quantised into an equivalent classical, deterministic solution. We explore the ability to extend this de-quantisation to further cases, and examine with more detail when de-quantisation is possible, both with respect to the Deutsch–Jozsa problem, as well as in more general cases.     

Inferring (Biological) Signal Transduction Networks via Transitive Reductions of Directed Graphs

In this paper we consider the p-ary transitive reduction (TR _p ) problem where p>0 is an integer; for p=2 this problem arises in inferring a sparsest possible (biological) signal transduction network consistent with a set of experimental observations with a goal to minimize false positive inferences even if risking false negatives. Special cases of TR _p have been investigated before in different contexts; the best previous results are as follows:

System Equivalence for AR-Systems over Rings—with an Application to Delay-Differential Systems

In this paper the notion of autoregressive systems over an integral domain ? is introduced, as a generalization of AR-systems over the rings ℝ[s] and ℝ[s,s ⁻¹]. The interpretation of the dynamics represented by a matrix over ? is fixed by the choice of a module ℳ over ?, consisting of all time-trajectories under consideration. In this setup the problem of system equivalence is studied: when do two different AR-representations characterize the same behavior? This problem is solved using a ring extension of ?, that explicitly depends on the choice of the module ℳ of all time-trajectories. In this way the usual divisibility conditions on the system defining matrices can be recovered. The results apply to the class of delay-differential systems with (in)commensurable delays. In this particular application, the ring extension of ? is characterized explicitly. Date received: May 13, 1998. Date revised: December 22, 1998.