A connection between supermodular ordering and positive/negative association

In this paper, we show that a vector of positively/negatively associated random variables is larger/smaller than the vector of their independent duplicates with respect to the supermodular order. In that way, we solve an open problem posed by Hu (Chinese J. Appl. Probab. Statist. 16 (2000) 133) refering to whether negative association implies negative superadditive dependence, and at the same time to an open problem stated in Müller and Stoyan (Comparison Methods for Stochastic Modes and Risks, Wiley, Chichester, 2002) whether association implies positive supermodular dependence. Therefore, some well-known results concerning sums and maximum partial sums of positively/negatively associated random variables are obtained as an immediate consequence. The aforementioned result can be exploited to give useful probability inequalities. Consequently, as an application we provide an improvement of the Kolmogorov-type inequality of Matula (Statist. Probab. Lett. 15 (1992) 209) for negatively associated random variables. Moreover, a Rosenthal-type inequality for associated random variables is presented.     

A distributed social choice protocol for combinatorial domains

In this paper, we study the problem of collective decision-making over combinatorial domains, where the set of possible alternatives is a Cartesian product of (finite) domain values for each of a given set of variables, and these variables are not preferentially independent. Due to the large alternative space, most common rules for social choice cannot be directly applied to compute a winner. In this paper, we introduce a distributed protocol for collective decision-making in combinatorial domains, which enjoys the following desirable properties: (i) the final decision chosen is guaranteed to be a Smith member; (ii) it enables distributed decision-making and works under incomplete information settings, i.e., the agents are not required to reveal their preferences explicitly; (iii) it significantly reduces the amount of dominance testings (individual outcome comparisons) that each agent needs to conduct, as well as the number of pairwise comparisons; (iv) it is sufficiently general and does not restrict the choice of preference representation languages.     

The training institution efficiency of the semiconductor institute programme in Taiwan—application of spatiotemporal ICA with DEA approach

Despite the fact that Taiwan’s high-tech industry has gradually secured a leading position in the world, enterprises in Taiwan have striven to strengthen their technical advancement by providing employees with various internal or external training programmes. These institutional training programmes are designed to sustain competitive advantage, enhance the quality of manpower and improve operational efficiency. Much literature assesses the efficiency of an internal training programme that is initiated by a firm, but only a little literature studies the efficiency of an external training programme that is led by a government. Various efficiency measurement tools, such as conventional statistical methods and non-parametric methods, have been successfully developed in the literature. Among these tools, the data envelopment analysis (DEA) approach is one of the most widely discussed. However, the DEA's capability to discriminate efficient decision-making units from inefficient decision-making units requires much improvement (Adler and Yazhemsky). In this paper, a two-stage approach of integrating spatiotemporal independent component analysis (stICA) and DEA is developed for efficiency measurement. stICA is used to search for latent source signals where no relevant signal mixture mechanisms are available; and DEA is used to measure the relative efficiencies of decision-making units (DMUs). We suggest using stICA first to extract the input variables for generating independent components (IC), then selecting the ICs representing the independent sources of input variables, and finally inputting the selected ICs as new variables in the DEA model. To find the effects of environmental variables on the estimated efficiency scores, the Tobit–Bayes (censored) regression is applied. A simulated dataset and the training institution dataset provided by the Semiconductor Institute in Taiwan is used for analysis. The empirical result shows that the proposed method can not only separate performance differences between the training institutions but also improve the discriminatory capability of the DEA's efficiency measurement. The study results can serve as a reference for training institutions wishing to enhance their training efficiency.     

Uniqueness and stability of the minimizer for a binary functional arising in an inverse heat conduction problem

The local well-posedness of the minimizer of an optimal control problem is studied in this paper. The optimization problem concerns an inverse problem of simultaneously reconstructing the initial temperature and heat radiative coefficient in a heat conduction equation. Being different from other ordinary optimization problems, the cost functional constructed in the paper is a binary functional which contains two independent variables and two independent regularization parameters. Particularly, since the status of the two unknown coefficients in the cost functional are different, the conjugate theory which is extensively used in single-parameter optimization problems cannot be applied for our problem. The necessary condition which must be satisfied by the minimizer is deduced. By assuming the terminal time T is relatively small, an L² estimate regarding the minimizer is obtained, from which the uniqueness and stability of the minimizer can be deduced immediately.     

A complex multi-attribute large-group PLS decision-making method in the interval-valued intuitionistic fuzzy environment

In the complex multi-attribute large-group decision-making (CMALGDM) problems in interval-valued intuitionistic fuzzy (IVIF) environment, attributes of the alternatives are often stratified and correlated. This paper proposes a decision-making method for these problems based on partial least squares (PLS) path modelling, which not only fully exploits the decision information of decision makers (DMs), but also effectively addresses the relativity problem in the decision attributes and objectively assigned weights to the primary decision attributes (i.e., “latent variables for decision making”). The method can be outlined in three steps. First, a two-stage method is proposed to transform the interval-valued intuitionistic fuzzy number (IVIFN) samples into single-valued samples. In this step, an improved C-OWA operator is first given to transform the IVIFN samples into intuitionistic fuzzy number (IFN) samples, which makes the preference information of the DMs more objectively aggregated. Then a proposed membership-based method is applied to reduce the information loss and transform the IFN samples into single-valued samples. Second, the estimated values and weights of the “latent variables for decision-making” are obtained by means of the PLS path modelling algorithm. Finally, a multi-alternative sorting method is devised in accordance with the estimated values and weights. An example is provided to illustrate the proposed technique and evaluate its feasibility and validity.     

Efficiency measurement using independent component analysis and data envelopment analysis

Efficiency measurement is an important issue for any firm or organization. Efficiency measurement allows organizations to compare their performance with their competitors’ and then develop corresponding plans to improve performance. Various efficiency measurement tools, such as conventional statistical methods and non-parametric methods, have been successfully developed in the literature. Among these tools, the data envelopment analysis (DEA) approach is one of the most widely discussed. However, problems of discrimination between efficient and inefficient decision-making units also exist in the DEA context (Adler and Yazhemsky, 2010). In this paper, a two-stage approach of integrating independent component analysis (ICA) and data envelopment analysis (DEA) is proposed to overcome this issue. We suggest using ICA first to extract the input variables for generating independent components, then selecting the ICs representing the independent sources of input variables, and finally, inputting the selected ICs as new variables in the DEA model. A simulated dataset and a hospital dataset provided by the Office of Statistics in Taiwan’s Department of Health are used to demonstrate the validity of the proposed two-stage approach. The results show that the proposed method can not only separate performance differences between the DMUs but also improve the discriminatory capability of the DEA’s efficiency measurement.     

The Design of axisymmetric ducts for incompressible flow with vorticity.

In this paper a numerical algorithm is described for solving the boundary value problem associated with axisymmetric, inviscid, incompressible, rotational (and irrotational) flow in order to obtain duct wall shapes from prescribed wall velocity distributions. The governing equations are formulated in terms of the stream function and the function as independent variables where for irrotational flow can be recognized as the velocity potential function, for rotational flow ceases being the velocity potential function but does remain orthogonal to the stream lines. A numerical method based on finite differences on a uniform mesh is employed. The technique described is capable of tackling the so–called inverse problem where the velocity wall distributions are prescribed from which the duct wall shape is calculated, as well as the direct problem where the velocity distribution on the duct walls are calculated from prescribed duct wall shapes. The two different cases as outlined in this paper are in fact boundary value problems with Neumann and Dirichlet boundary conditions respectively. Even though both approaches are discussed, only numerical results for the case of the Dirichlet boundary conditions are given. A downstream condition is prescribed such that cylindrical flow, that is flow which is independent of the axial coordinate, exists. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Fuzzy random regression based multi-attribute evaluation and its application to oil palm fruit grading

Multi-attribute decision-making is usually concerned with weighting alternatives, thereby requiring weight information for decision attributes from a decision maker. However, the assignment of an attribute’s weight is sometimes difficult, and may vary from one decision maker to another. Additionally, imprecision and vagueness may affect each judgment in the decision-making process. That is, in a real application, various statistical data may be imprecise or linguistically as well as numerically vague. Given this coexistence of random and fuzzy information, the data cannot be adequately treated by simply using the formalism of random variables. To address this problem, fuzzy random variables are introduced as an integral component of regression models. Thus, in this paper, we proposed a fuzzy random multi-attribute evaluation model with confidence intervals using expectations and variances of fuzzy random variables. The proposed model is applied to oil palm fruit grading, as the quality inspection process for fruits requires a method to ensure product quality. We include simulation results and highlight the advantage of the proposed method in handling the existence of fuzzy random information.     

Uniformly continuous dependence of a solution to a controlled functional operator equation on a shift of control

We establish sufficient conditions for the uniform (with respect to the set of admissible controls) continuous dependence of a solution to a controlled functional operator equation on a shift of control along a vector of independent variables. The shift of control may mean, in particular, some time delay (or outstripping) of the control. We illustrate the use of general results by an example of a mixed boundary-value problem associated with a wave equation.     

Disconnected optimal trajectories

The Bolza problem of the calculus of variations in modern control notation is extended in scope to include situations in which a number of subarcs occur in a variety of ways. The subarcs are allowed to be overlapping and/or separated. This allows for several subarcs to occur in the same interval of the independent variable and also admits subarcs which are separated by jumps in the independent and state variables. In addition, the differential constraining equations and the integral quantity to be extremized are permitted to have different form from subarc to subarc.The necessary conditions for the extended Bolza problem are obtained by examining a related functional. Whereas the optimizing conditions for the state and control variables for each subarc are given by the usual Euler equations, new conditions associated with the end points of the subarcs are derived using ordinary theory of maxima and minima.The results presented here can be applied to a wide range of space trajectory problems. For some special cases, the theory reduces to results previously obtained and recorded elsewhere. A number of sample problems illustrating the theory are presented. The examples include the problem of inserting two payloads into separate orbits with one vehicle having two upper stages ignited simultaneously and a two-vehicle, dual-rendezvous problem.This work was supported in part by the National Aeronautics and Space Administration, Grant No. NSG-580.     

The Homotopy Perturbation Renormalization Group Method to Solve the WKB Problem with Turn Points

In this paper, we give the homotopy perturbation renormalization group method, this is a new method for turning point problem. Using this method, the independent variables are introduced by transformation without introducing new related variables and no matching is needed. The WKB approximation method problem can be solved.     

Epsilon-Ritz Method for Solving a Class of Fractional Constrained Optimization Problems

In this paper, epsilon and Ritz methods are applied for solving a general class of fractional constrained optimization problems. The goal is to minimize a functional subject to a number of constraints. The functional and constraints can have multiple dependent variables, multiorder fractional derivatives, and a group of initial and boundary conditions. The fractional derivative in the problem is in the Caputo sense. The constrained optimization problems include isoperimetric fractional variational problems (IFVPs) and fractional optimal control problems (FOCPs). In the presented approach, first by implementing epsilon method, we transform the given constrained optimization problem into an unconstrained problem, then by applying Ritz method and polynomial basis functions, we reduce the optimization problem to the problem of optimizing a real value function. The choice of polynomial basis functions provides the method with such a flexibility that initial and boundary conditions can be easily imposed. The convergence of the method is analytically studied and some illustrative examples including IFVPs and FOCPs are presented to demonstrate validity and applicability of the new technique.     

T‐complete functions for thin and thick plates on elastic foundation

This article deals with Trefftz functional systems for thin and thick plates on one‐ and two‐parameter Winkler foundation. The T‐complete set is derived by solving the homogeneous equations of the problem. This can be done with the method of separation of variables. For each separation parameter we deal with ordinary, linear differential equations (4th order for the Kirchhoff plate and set of fourth‐ and second‐order equations for the Reissner‐Mindlin plate) so the demanded number of fundamental solutions (linearly independent) is equal to the order of equation. © 2004 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2005     

凑合反推法和弹性理论中的多变量广义变分原理

详细介绍了如何应用凑合反推法(semi-inverse method)构造弹性理论中的两类独立变量的广义变分原理(包括熟知的Hellinger-Reissner变分原理,Hu-Washizu变分原理)及三类独立变量的广义变分原理(钱伟长广义变分原理) 。应用凑合反推法还可以清楚地看出各变量之间的约束关系,从而再一次证明了Hu-Washizu变分原理实际上是两类独立变量的广义变分原理。     

基于改进熵权法的区间直觉模糊TOPSIS方法

本文对区间直觉模糊信息的TOPSIS多属性决策方法进行了研究。在属性权重信息完全未知的情况下,通过研究熵权法以及区间直觉模糊集本身的一些性质特点,将熵权法拓展到区间直觉模糊环境中来确定属性权重,进而提供了一种可直接利用评估信息的新的TOPSIS决策方法。该方法不仅拓展了传统熵权法的应用范围,而且不需要决策者事先给出权重信息,结果更加客观和可靠。应用实例表明该方法的可行性和有效性,具有推广应用价值。     

Robust Averaged Control of Vibrations for the Bernoulli–Euler Beam Equation

This paper proposes an approach for the robust averaged control of random vibrations for the Bernoulli–Euler beam equation under uncertainty in the flexural stiffness and in the initial conditions. The problem is formulated in the framework of optimal control theory and provides a functional setting, which is so general as to include different types of random variables and second-order random fields as sources of uncertainty. The second-order statistical moment of the random system response at the control time is incorporated in the cost functional as a measure of robustness. The numerical resolution method combines a classical descent method with an adaptive anisotropic stochastic collocation method for the numerical approximation of the statistics of interest. The direct and adjoint stochastic systems are uncoupled, which permits to exploit parallel computing architectures to solve the set of deterministic problem that arise from the stochastic collocation method. As a result, problems with a relative large number of random variables can be solved with a reasonable computational cost. Two numerical experiments illustrate both the performance of the proposed method and the significant differences that may occur when uncertainty is incorporated in this type of control problems.     

Two novel FMCDM methods for alternative-fuel buses selection

In this paper, we consider the problem of alternative-fuel buses selection using two novel fuzzy multiple criteria decision-making (MCDM) methods. Several types of fuels are considered as fuel modes, i.e., electricity, fuel cell (hydrogen), and methanol. For the purpose of determining appropriate fuel buses, many factors including quantitative and qualitative ones such as efficiency, price, and capability must be taken into account. In the first proposed method, linguistic variables are used to assess the ratings and weights for factors. These linguistic ratings can be expressed in trapezoidal or triangular fuzzy numbers. Then, a hierarchical MCDM method based on fuzzy-sets theory is proposed to deal with the fuel buses selection problem. To simultaneously determine the ranking order of all alternatives based on the concept of the TOPSIS by calculating the distances to the both fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS), a closeness coefficient is defined. In the second presented method we extend preference selection index (PSI) method for fuzzy environment. In this method performance ratings of criteria evaluate by linguistic variable which can be expressed in trapezoidal fuzzy numbers. Finally, an example is shown to highlight the procedure of the proposed methods and compare the results of these methods with each other.     

A rule-based risk decision-making approach and its application in China's customs inspection decision

This paper addresses a kind of risk decision-making problem existing widely in public administration and business management, which is characterized by (1) occurrence probabilities of states of nature can be estimated by analysing historical observations, but historical observations of different objects are unhomogeneous, (2) the relation between observations and occurrence probabilities of states of nature are affected by some qualitative and quantitative indicators, (3) it is a real-time decision-making problem, that is, there are many decisions for different objects to be made in a limited time, (4) considering decision's execution, impact of resource constrains is an important issue in decision-making process. In this paper, we develop a rule-based approach to address the problem. In the proposed approach, a two-step clustering method is employed to classify objects into categories, and observations in each category can be approximately viewed as homogeneous. For objects in each category, occurrence probabilities of states of nature are estimated by logistic regression, and the decision rule is obtained through solving an optimization model, which is to minimize the total decision risks while satisfying resource constrains. Effect and efficacy of our approach are illustrated through its application to China's customs inspection decision.     

Pseudospectral method for transient viscoelastic flow in an axisymmetric channel

A new pseudospectral method for simulating transient viscoelastic flows is presented. The governing equations are a system of seven first-order equations of mixed type. The essential features of the method are (i) all seven independent flow variables are represented on a common Chebyshev-Gauss-Lobatto grid; (ii) the pressure is treated in such a way as to give a globally divergence-free velocity field, i.e., the divergence of the velocity field vanishes globally within the region, and (iii) different time scales pertaining within the hyperbolic constitutive equations are treated using the splitting technique of LeVeque and Yee originally proposed in a finite-difference context. The method is applied to transient axisymmetric flow of an Oldroyd B fluid in a channel formulated in two ways: (I) as an initial boundary-value problem, and (II) as a body-force problem. © 1993 John Wiley & Sons, Inc.     

Lax pairs and a new spectral method for linear and integrable nonlinear PDEs

A new transform method for solving initial-boundary value problems for linear and integrable nonlinear PDEs in two independent variables has been recently introduced in [1]. For linear PDEs this method involves: (a) formulating the given PDE as the compatibility condition of two linear equations which, by analogy with the nonlinear theory, we call a Lax pair; (b) formulating a classical mathematical problem, the so-called Riemann-Hilbert problem, by performing a simultaneous spectral analysis of both equations defining the Lax pair; (c) deriving certain global relations satisfied by the boundary values of the solution of the given PDE. Here this method is used to solve certain problems for the heat equation, the linearized Korteweg-deVries equation and the Laplace equation. Some of these problems illustrate that the new method can be effectively used for problems with complicated boundary conditions such as changing type as well as nonseparable boundary conditions. It is shown that for simple boundary conditions the global relations (c) can be analyzed using only algebraic manipulations, while for complicated boundary conditions, one needs to solve an additional Riemann-Hilbert problem. The relationship of this problem with the classical Wiener-Hopf technique is pointed out. The extension of the above results to integrable nonlinear equations is also discussed. In particular, the Korteweg-deVries equation in the quarter plane is linearized.