高效安全向量计算及其推广

安全多方计算是密码学的一个重要研究方向,也是目前国际密码学界的研究热点.因为许多实际问题都可以用向量来描述,研究向量的保密计算具有重要的理论与实际意义.目前,关于向量保密计算问题大多是在整数集上进行研究,关于有理数向量问题的研究很少.在此主要研究有理数域上向量的安全多方计算问题,包括向量点积、向量相等、向量优势等问题,设计了安全高效的计算协议,扩大了向量保密计算的应用范围.对这些协议的安全性分析和效率分析表明,它们在安全性和效率方面与现有协议相比具有明显优势.并且利用所设计的协议解决了一些新的向量问题和计算几何问题.     

基于投影及优势度的不确定语言群决策方法

针对属性权重信息不完全的多粒度不确定语言多属性群决策问题,提出一种基于投影及优势度的群决策方法.该方法采用连续区间二元语义的有序加权调和平均(ITC-OWH)算子将多粒度不确定语言评价矩阵转化为二元语义决策矩阵,基于投影法构建目标规划模型,从而确定单个决策者的属性权重向量.在每个决策者之下,计算任意2个方案之间比较的综合属性优势度,根据综合优势度矩阵及决策者权重向量获得群体综合优势度矩阵,由各方案的总优势度获取方案的排序结果.最后,将提出的群决策方法应用到潜艇研制方案遴选问题中,验证了该方法的可行性与有效性.     

Interactive Evolutionary Multi-Objective Optimization Algorithm Using Cone Dominance

As the number of objectives increases, the performance of the Pareto dominance-based Evolutionary Multi-objective Optimization (EMO) algorithms such as NSGA-II, SPEA2 severely deteriorates due to the drastic increase in the Pareto-incomparable solutions. We propose a sorting method which classifies these incomparable solutions into several ordered classes by using the decision maker's (DM) preference information. This is accomplished by designing an interactive evolutionary algorithm and constructing convex cones. This method allows the DMs to drive the search process toward a preferred region of the Pareto optimal front. The performance of the proposed algorithm is assessed for two, three, and four-objective knapsack problems. The results demonstrate the algorithm's ability to converge to the most preferred point. The evaluation and comparison of the results indicate that the proposed approach gives better solutions than that of NSGA-II. In addition, the approach is more efficient compared to NSGA-II in terms of the number of generations required to reach the preferred point.     

基于物元特征关联度及网络层次分析法的评价及应用

本文基于物元分析理论及MINE算法的思想,提出了物元特征关联度的定义;将物元特征关联度应用到网络层次分析法（ANP）评价方法中,构造了股票价值评估的客观赋权模型,并给出了股票价值评估的ME-ANP算法,以上市公司的财务数据为基础,对股票价值给予具体评估,同时说明了本文所构建的模型及算法的有效性。     

基于统计占优分析的变异测试

为数众多的变异体产生的高昂测试代价严重影响了变异测试技术在实际程序中的应用.为了大幅度减少弱变异测试中变异体的数量,提出基于统计占优分析的变异体约简方法.该方法首先利用变异前后的语句构造变异分支,并将所有变异分支集成到原程序中,形成新的被测程序;然后,通过统计测试用例对各个变异分支的覆盖信息,确定变异分支之间的占优关系;最后得到非被占优分支集,其对应的变异体就是约简后的变异体.将该方法用于8个程序的测试,结果表明:该方法能够约简平均90%的变异体,从而显著提高了变异测试的效率.     

随机需求下多风险偏好零售商的供应链库存决策和协调

考虑由单个风险中性供应商和?? 个风险偏好零售商组成的供应链系统. 假设市场需求是随机的, 且每个零售商面临的需求与其订货量成正比, 采用平均CVaR 准则刻画零售商的风险偏好. 当零售商对称时, 得到系统总的均衡订货量关于零售商数量和风险偏好系数的单调性; 证明当风险偏好系数满足一定条件时, 批发价契约可以使供应链协调; 随机大需求导致系统较高的均衡订货量. 最后通过数值例子表明了需求可变性对系统总的均衡订货量的影响.

     

Dominance-based rough set approach and knowledge reductions in incomplete ordered information system

Many methods based on the rough set to deal with incomplete information systems have been proposed in recent years. However, they are only suitable for the incomplete systems with regular attributes whose domains are not preference-ordered. This paper thus attempts to present research focusing on a complex incomplete information system—the incomplete ordered information system. In such incomplete information systems, all attributes are considered as criterions. A criterion indicates an attribute with preference-ordered domain. To conduct classification analysis in the incomplete ordered information system, the concept of similarity dominance relation is first proposed. Two types of knowledge reductions are then formed for preserving two different notions of similarity dominance relations. With introduction of the approximate distribution reduct into the incomplete ordered decision system, the judgment theorems and discernibility matrixes associated with four novel approximate distribution reducts are obtained. A numerical example is employed to substantiate the conceptual arguments.     

Interleaving Guidance in Evolutionary Multi-Objective Optimization

In this paper, we propose a framework that uses localization for multi-objective optimization to simultaneously guide an evolutionary algorithm in both the decision and objective spaces. The localization is built using a limited number of adaptive spheres （local models） in the decision space. These spheres axe usually guided, using some direction information, in the decision space towards the areas with non-dominated solutions. We use a second mechanism to adjust the spheres to specialize on different parts of the Paxeto front by using a guided dominance technique in the objective space. Through this interleaved guidance in both spaces, the spheres will be guided towards different parts of the Paxeto front while also exploring the decision space efficiently. The experimental results showed good performance for the local models using this dual guidance, in comparison with their original version.     

基于优势关系的信息系统与形式概念分析

对形式概念分析在基于优势关系的信息系统中的应用进行了讨论,证明了由基于优势关系的信息系统导出的形式背景中的对象粒与优势类是等价的,同时对象粒协调集与优势协调集是等价的。     

鲁棒的逆Nyquist阵列(RINA)设计方法

通过大量的数值计算和回归分析找出了矩阵的对角优势度与特征值摄动量的关系,进而 提出一种鲁棒的逆Nyquist阵列(RINA)设计方法,该方法既保持了INA方法的优点,又 使控制系统具有希望的鲁棒性.并针对伪对角化方法存在的不足之处提出一种"双环优势化" 方法.此外,也澄清了Doyle和Steln关于INA方法缺乏鲁棒性的提法.