The effect of transformations on the approximation of univariate (convex) functions with applications to Pareto curves

In the literature, methods for the construction of piecewise linear upper and lower bounds for the approximation of univariate convex functions have been proposed. We study the effect of the use of transformations on the approximation of univariate (convex) functions. In this paper, we show that these transformations can be used to construct upper and lower bounds for nonconvex functions. Moreover, we show that by using such transformations of the input variable or the output variable, we obtain tighter upper and lower bounds for the approximation of convex functions than without these approximations. We show that these transformations can be applied to the approximation of a (convex) Pareto curve that is associated with a (convex) bi-objective optimization problem.     

Thermodynamic consistency of experimental VLE data for asymmetric binary mixtures at high pressures

A thermodynamic consistency of isothermal vapor–liquid equilibrium data for 9 non-polar and 8 polar binary asymmetric mixtures at high pressures has been evaluated. A method based on the isothermal Gibbs–Duhem equation was used for the test of thermodynamic consistency using a Φ–Φ approach. The Peng–Robinson equation of state coupled with the Wong–Sandler mixing rules were used for modeling the vapor–liquid equilibrium (VLE) within the thermodynamic consistency test. The VLE parameters calculations for asymmetric mixtures at high pressures were highly dependent on bubble pressure calculation, making more convenient to eliminate the data points yielding the highest deviations in pressure. However the results of the thermodynamic consistencies test of experimental data for many cases were found not fully consistent. As a result, the strategies for solving these problems were discussed in detailed.     

一种基于RTO的业务排序算法

业务影响分析是业务连续性计划中较为关键的一步,其最终目标是对企业中业务的重要性进行排序。文中的目的是提出一种企业在进行灾难恢复时,各个业务过程之间恢复优先顺序的排序算法。该算法在设计时基于RTO进行排序,并考虑了业务之间的相互依赖关系对恢复顺序的影响。通过实验显示了该算法的合理性：使用该算法可以更好地实施业务影响分析,缩短分析时间,从而提高整个业务连续性实施过程的效率。     

基于Contourlet视觉模型和奇异值分解的图像质量评价

针对基于像素值的图像质量评价方法忽视图像结构信息和需要完全参考图像等问题,提出了一种基于Contourlet域奇异值分解CW-SVD,部分参考图像质量评价方法(contourlet weighted singular value decomposition)。在Contourlet域中,利用奇异值向量对图像结构的表征能力,结合人眼视觉敏感性确定每个子带的视觉权重,得到每个子带的评价测度,再综合得出图像的最终评价指标。实验表明,该方法应用于4种类型的降质图像质量评价时,比峰值信噪比(PSNR、MSSIM)等算法具有更好的稳定性和更好的主客观评价一致性。     

An iterative approach to solve multiobjective linear fractional programming problems

This paper suggests an iterative parametric approach for solving multiobjective linear fractional programming (MOLFP) problems which only uses linear programming to obtain efficient solutions and always converges to an efficient solution. A numerical example shows that this approach performs better than some existing algorithms. Randomly generated MOLFP problems are also solved to demonstrate the performance of new introduced algorithm.     

Solving a bi-objective Transportation Location Routing Problem by metaheuristic algorithms

In this work we consider a Transportation Location Routing Problem (TLRP) that can be seen as an extension of the two stage Location Routing Problem, in which the first stage corresponds to a transportation problem with truck capacity. Two objectives are considered in this research, reduction of distribution cost and balance of workloads for drivers in the routing stage. Here, we present a mathematical formulation for the bi-objective TLRP and propose a new representation for the TLRP based on priorities. This representation lets us manage the problem easily and reduces the computational effort, plus, it is suitable to be used with both local search based and evolutionary approaches. In order to demonstrate its efficiency, it was implemented in two metaheuristic solution algorithms based on the Scatter Tabu Search Procedure for Non-Linear Multiobjective Optimization (SSPMO) and on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) strategies. Computational experiments showed efficient results in solution quality and computing time.     

主客观组合赋权的灰色决策模型及其在消费者决策中的运用

现实中许多抽象系统的数值并不能精确地得到,在多属性决策过程中,其属性值多以模糊数或者区间灰数的形式表示,属性权重也受到主观因素和客观因素的影响,针对此类问题,以属性值为区间灰数的多属性决策问题为出发点,采用主客观结合的赋权方式,提出了基于区间距离的灰色相对关联度分析方法,构建了灰色决策模型,并通过消费者决策实例进行了分析,模型是对传统灰色决策模型的拓展,具有更广泛的应用性和实用性.     

半马氏环境连续时间马氏决策过程：平均准则

本文讨论半马氏环境连续时间马氏决策过程中的平均准则．首先讨论了半马氏报酬过程中的逼近问题，进而讨论平均目标函数逼近问题。     

Incorporating additional meta-objectives into the extended lexicographic goal programming framework

This paper introduces two new meta-objectives into the extended goal programming framework. The first meta-objective is the number of unmet goals and the second is a measure of closeness to the pairwise comparisons given by the decision maker. These complement the original two meta-objectives of the weighted sum of deviations and the maximal weighted deviation to provide a flexible four meta-objective framework. Lexicographic and non-lexicographic representations of the framework are developed. An example relating to transportation is solved in both the lexicographic and non-lexicographic forms. Weight sensitivity analysis is applied to the meta-weight parameters for the non-lexicographic case in order to find a range of available distinct solutions.