Incremental analysis for MCDM with an application to group TOPSIS

The study aims to exploit incremental analysis or marginal analysis to overcome the drawbacks of ratio scales utilized in various multi-criteria or multi-attribute decision making (MCDM/MADM) techniques. In the proposed 11-step procedure, multiple criteria of alternatives are first reorganized as two categories – benefits and costs – and decision information will be manipulated separately. The performances of alternatives are then evaluated on their incremental benefit–cost ratio, and the rank can be obtained by applying the group TOPSIS (technique for order preference by similarity to ideal solution) model (Shih et al., 2007). Two representations of cost, i.e., a cost index and utility index, are proposed in the model to better-fit real-world situations. In addition, some considerations on costs and input–output relations are also discussed in order to understand the essentials of incremental analysis. In the final part, a case of robot selection demonstrates the suggested model to be both robust and efficient in a group decision-making environment.     

A generalized preconditioned HSS method for non-Hermitian positive definite linear systems

Based on the HSS (Hermitian and skew-Hermitian splitting) and preconditioned HSS methods, we will present a generalized preconditioned HSS method for the large sparse non-Hermitian positive definite linear system. Our method is essentially a two-parameter iteration which can extend the possibility to optimize the iterative process. The iterative sequence produced by our generalized preconditioned HSS method can be proven to be convergent to the unique solution of the linear system. An exact parameter region of convergence for the method is strictly proved. A minimum value for the upper bound of the iterative spectrum is derived, which is relevant to the eigensystem of the products formed by inverse preconditioner and splitting. An efficient preconditioner based on incremental unknowns is presented for the actual implementation of the new method. The optimality and efficiency are effectively testified by some comparisons with numerical results.     

Solving symmetric mixed-model multi-level just-in-time scheduling problems

The generation of leveled production schedules is of high importance for mixed-model assembly lines whose parts and materials are supplied just-in-time by multi-level production processes. The Output Rate Variation problem is the standard mathematical representation of this complex level scheduling problem and has been extensively studied by research thus far. This work identifies novel symmetries in solution sequences of this problem class and shows how these insights can be used to improve exact solution procedures presented in the literature. The effectiveness of the modifications is evaluated by a computational study.     

Nonsmooth nonconvex optimization approach to clusterwise linear regression problems

Clusterwise regression consists of finding a number of regression functions each approximating a subset of the data. In this paper, a new approach for solving the clusterwise linear regression problems is proposed based on a nonsmooth nonconvex formulation. We present an algorithm for minimizing this nonsmooth nonconvex function. This algorithm incrementally divides the whole data set into groups which can be easily approximated by one linear regression function. A special procedure is introduced to generate a good starting point for solving global optimization problems at each iteration of the incremental algorithm. Such an approach allows one to find global or near global solution to the problem when the data sets are sufficiently dense. The algorithm is compared with the multistart Späth algorithm on several publicly available data sets for regression analysis.     

Stability and stabilization by output feedback control of positive Takagi–Sugeno fuzzy discrete-time systems with multiple delays

This paper deals with the problem of stabilization by output feedback control of Takagi–Sugeno (T–S) fuzzy discrete-time systems with a fixed delay by linear programming (LP) and cone complementarity while imposing positivity in closed-loop. The stabilization conditions are derived using the single Lyapunov–Krasovskii Functional (LKF). An example of a real plant is studied to show the advantages of the design procedure.     

输入为基础输出为驱动①--浅谈大学英语听说课堂中学生听说能力的培养

根据第二语言习得的输入与输出理论,“听”和“说”分别属于语言输入和输出。在设计英语听说课堂教学活动时,教师应将“听”和“说”有机结合起来,“以说带听”巧妙引入话题;“听前预测”、“听中筛选”提高听力效率;“以听促说”提高语言应用能力。在大学英语听说课上,教师合理处理“听与说”的关系,认真设计“听说”活动,使“听说”互为因果,相辅相成才能促进有效输入和积极输出,从而促进学生“听说”能力的培养。     

Effect of gas convection induced by cross-field discharge in a copper vapor laser

Magnetic field has been applied to a copper vapor laser with an intention of improving the laser characteristics by inner gas convection. The convection induced by the J×B cross-field discharge (the Lorentz force) is used for partially replacing or mixing the laser medium in a highly heated discharged region with relatively cold gas surrounding the region. It is observed that the output power increases with the increase of the magnetic field. A 23% increase in the output power is obtained with a magnetic field of 150 gauss. The cross-field discharge causes an increase in the peak discharge voltage and a reduction in the initial part of discharge current (Phantom current). Based on the results observed, the possible mechanisms for increasing the power are discussed.     

一类加权半隐格式增量未知元方法的稳定性和误差估计

本文提出一类基于一维热传导方程数值求解的增量未知元方法加权半隐格式,并由此给出分析稳定性和整体截断误差的新方法．我们引入源于Laplace算子的两组基底,使得放大矩阵易于分析;我们利用IU性质和矩阵运算技巧,严格证明了所述加权格式的稳定性充分条件和全局误差估计,这些结果本质上优于1/4≤θ≤3/4条件下的常见情形．所得结论为恢复初始误差带来可能,为选择最优加权半隐格式提供了理论依据．     

改进的三极管特性测试实验

介绍了一种测试三极管特性的新的实验方法,与旧方法的对比表明新方法更快速、准确、实用。