给定限期条件下的应急系统优化选址模型及算法

针对应急系统的特点,提出了在满足应急系统时间紧迫性的前提下,基于系统的费用最小的数学模型,并给出了相应的求解算法,并从理论上证明了该应急系统模型求解方法的正确性。     

Pipage Rounding: A New Method of Constructing Algorithms with Proven Performance Guarantee

The paper presents a general method of designing constant-factor approximation algorithms for some discrete optimization problems with assignment-type constraints. The core of the method is a simple deterministic procedure of rounding of linear relaxations (referred to as pipage rounding). With the help of the method we design approximation algorithms with better performance guarantees for some well-known problems including MAXIMUM COVERAGE, MAX CUT with given sizes of parts and some of their generalizations.     

遗传算法优化神经网络及信用评价研究

研究关于公司神经网络信用评估问题的现状,提出遗传算法辅助网络训练策略(优化后的网络称为进化网络),克服传统网络建模中产生的局部极小缺陷。建立了适合于我国商业企业的信用评分指标体系;然后依据该指标体系建立了基于进化神经网络的信用评估模型;最后,利用样本公司实际指标数据对该模型的评分效果进行了比较研究。     

大型供应链设计的基本数学模型与算法研究

随着信息技术与全球经济一体化的发展,供应链管理成为全球管理科学的研究热点。本文在分析国内外各种关于供应链设计的数学模型与算法的基础上,提出了具有普遍性意义且简单易行的MIP供应链设计的数学模型以及求解供应链问题的有界变量广义上界算法。实例计算表明,提出的模型和方法是可靠实用的。     

An Exploration of “Superb Competences” in College Teachers in the Context of U-Learning

Ubiquitous learning (U-learning), a potential shortcut for China to modernize its education, is treated in this discussion as a mentality and means for citizens in high-tech society to seek a lifelong education. Thus situated, this article presents an exploration of “superb competences”—material intelligence, internet thinking, and brain-related neuro knowledge—in college teachers outside their trained professional areas. It is believed that once the teachers are equipped with the material intelligence, internet thinking, and brain-related neuro knowledge, real U-learning practice is ensured and its rationale will be developed. Material intelligence and internet thinking are evolved from and closely related to technological development, and therefore constitute the essential requirements of U-learning in terms of technical and educational cognitive framework. A good knowledge of brain related neuroscience, the third competence, guarantees the scientific rooting of every element in the designing of U-leaning tasks, whose success resides in a serious respect of cognitive nature and rules of the brain. The building of such superb competences, as is argued at the end of the paper, relies on various supports, like policies and technological aids, from all levels of educational administration in the country as well as each individual teacher’s personal understanding and efforts.     

Higher-order Bayesian Approximations for Pseudo-posterior Distributions

The theory of higher-order asymptotics provides accurate approximations to posterior distributions for a scalar parameter of interest, and to the corresponding tail area, for practical use in Bayesian analysis. The aim of this article is to extend these approximations to pseudo-posterior distributions, e.g., posterior distributions based on a pseudo-likelihood function and a suitable prior, which are proved to be particularly useful when the full likelihood is analytically or computationally infeasible. In particular, from a theoretical point of view, we derive the Laplace approximation for a pseudo-posterior distribution, and for the corresponding tail area, for a scalar parameter of interest, also in the presence of nuisance parameters. From a computational point of view, starting from these higher-order approximations, we discuss the higher-order tail area (HOTA) algorithm useful to approximate marginal posterior distributions, and related quantities. Compared to standard Markov chain Monte Carlo methods, the main advantage of the HOTA algorithm is that it gives independent samples at a negligible computational cost. The relevant computations are illustrated by two examples.     

考虑零件三维装载约束带时间窗的循环取货路径问题研究

为提高车辆的可装载性,对考虑三维装载约束带时间窗的循环取货路径问题进行研究.在给定假设与约束条件的前提下,建立该问题的多目标数学模型,并设计用于问题求解的基于改进策略的启发式算法.数值实例的计算结果表明,该算法可有效求解考虑零件三维装载约束带时间窗的循环取货路径问题;且与时间窗优先法的求解结果相比,可大幅提高车辆的可装载性,并能有效减少不同车型车辆的投入数量.     

Computation of an efficient and robust estimator in a semiparametric mixture model

In this article, we propose an efficient and robust estimation for the semiparametric mixture model that is a mixture of unknown location-shifted symmetric distributions. Our estimation is derived by minimizing the profile Hellinger distance (MPHD) between the model and a nonparametric density estimate. We propose a simple and efficient algorithm to find the proposed MPHD estimation. Monte Carlo simulation study is conducted to examine the finite sample performance of the proposed procedure and to compare it with other existing methods. Based on our empirical studies, the newly proposed procedure works very competitively compared to the existing methods for normal component cases and much better for non-normal component cases. More importantly, the proposed procedure is robust when the data are contaminated with outlying observations. A real data application is also provided to illustrate the proposed estimation procedure.     

A new family of multivariate slash distributions

In this article, a new form of multivariate slash distribution is introduced and some statistical properties are derived. In order to illustrate the advantage of this distribution over the existing generalized multivariate slash distribution in the literature, it is applied to a real data set.     

材料发展对建筑装饰设计影响的研究

由材料发展引发的一系列关于建筑装饰设计创新的概念,其主要的目的就是更好将建筑装饰设计与材料运用结合起来。只有通过建筑装饰材料的更新与发展,才能达到将建筑装饰设计艺术、技术结合起来快速发展的目标。从建筑装饰材料发展的历史入手,分析建筑装饰材料使用现状,结合材料特性、绿色环保、智能材料、节能材料、低碳等角度对未来材料的可能性发展方向及其对建筑装饰设计的影响进行探讨,总结归纳材料发展对建筑装饰设计影响的一般性规律,促进建筑装饰设计文化的发展与繁荣,营造宜居人居环境。