一种最小测试用例集生成方法

测试用例的数量和质量决定软件测试的成本和有效性．该文提出了一种生成最小测试用例集的方法，该方法首先充分考虑测试目标中各个测试需求之间的相互关系，将满足测试需求的所有可用测试用例进行划分，根据划分的结果生成一个测试用例集，然后利用启发式算法、贪心算法或整数规划方法来消除冗余，对这个测试用例集进行进一步的简化．这种方法与已有方法相比，优点在于它可以生成满足所有测试需求的最小测试用例集．     

一种面向并行设计规划的快速布局模型与算法

面向并行设计规划的快速布局是高性能计算机概念设计不可缺少的重要手段,布局目标、布局对象、布局结果等方面的特殊性,决定了传统布局方法难以满足并行设计规划需求。针对巨型机概念设计需求,在传统芯片级与系统级布局规划方法基础上,提出一种面向并行设计规划的快速布局模型与算法。该算法是基于有向图分解模型的分级布局算法,将定时驱动布局思想引入结群过程,是集定时驱动布局、基于结群的布局、基于划分的布局和有向图分解为一体的快速布局算法。该算法被成功应用到某巨型机概念设计的并行设计规划过程。     

基于遗传算法的大规模矩形件优化排样

大规模矩形件优化排样是一个典型的组合优化问题，属于NP-hard问题．实际工程中对一个排样方案一般有满足“一刀切”的工艺要求，“一刀切”要求增加了对排样的约束．提出的优化算法，将矩形匹配分割算法作为遗传算法染色体的解码器实现一个排样方案，用遗传算法进行排样方案的全局搜索．算例比较表明，该算法可以求得满足“一刀切”约束的最优解．     

基于用户策略的Web服务动态选择方法研究

目前的Web服务选择方法主要是服务关键词语义和属性匹配、运行性能最优评估,未能很好考虑用户对服务质量的个性化需求.对用户需求、服务质量进行模型描述,结合用户策略给出了一个服务评估和选择算法,该算法根据服务请求者的满意度对候选服务进行评估和选择.与已有的服务性能选择方法相比,该方法更能满足个性化需求.     

Pro/CONCEPT问与答

Pro/CONCEPT问与答我们已经有用于很多概念设计的数字工具。为什么还需要另一套？Pro/CONCEPT是一套能满足您所有概念设计需求的经济型解决方案。集绘图和建模功能于一体的Pro/CONCEPT，可以替代您目前使用的许多概念设计系统，从而简化了您的数字系统，避免了它们之间的集成所     

多色集合的研究及在机械产品概念设计中应用

在多色集合这一信息处理工具的基础上，建立了面向离散系统建模与分析的多色集合模糊数学模型，给出按多色集合模糊数学模型进行设计的准则和机械产品概念设计的搜索算法。使用该搜索算法可以得到符合技术规范的若干可行产品方案，组成可行产品方案集；然后利用方案选择算法，可以在确定的可行产品方案集中选择出合理的产品方案；最后举例作了说明。     

船舶概念设计阶段的多目标优化与决策

船舶概念设计阶段,需要初步给定多组船型参数方案并从中优选出客观合理的某一方案.以散货船为研究对象,建立了以船舶造价、单位排水量船体阻力、相对回转直径为目标的船舶概念设计优化数学模型;应用改进的非支配解排序的多目标进化算法求解船舶概念设计多目标问题以获得Pareto解集.分析了主观赋权和客观赋权的优劣,提出采用线性叠加在层次分析法、变异系数法这两种主观赋权和客观赋权方法间求取组合赋权向量,将组合向量与TOPSIS法结合对所求Pareto解集进行方案排序.优化决策结果表明,改进的非支配解排序的多目标进化算法DW=36000t散货船概念设计优化能获得多组综合性能优良的船型方案,基于线性叠加的组合赋权TOPSIS决策策略能给出客观、有效的方案序列.这种二阶段的综合方法也能推广应用于船舶优化与决策其他领域.     

有时间窗物流配送车路由问题的改进遗传算法

给出了有时间窗物流配送车路由问题的数学模型．通过引入新颖交叉算子RC，构造了一种改进的遗传算法．实验结果表明．该算法在解决有时间窗的物流配送车路由问题时，比PMX及RC算子具有更优的性能，在满足所有需求点的前提下达到各评价指标的综合最优，是求解配送车路由问题的一个较好方案．     

非监督学习算法应用于异常检测的效果评估

目前的入侵检测系统普遍使用基于特征库的方法进行检测，这种方法需要已知类别标签的数据集来进行训练．而得到这种数据集的代价一般都很大。因此，我们对“非监督学习”算法应用于异常检测的检测效果进行了评估．我们共评估了三种算法-聚类算法、K-近邻算法和一类SVM算法，其结果令人满意。     

解约束多目标优化问题的一种鲁棒的进化算法

将约束条件与目标函数融合在一起，对有约束的多目标优化问题(MOP)建立了一种新的偏序关系，引入了约束占优的定义，并证明了在新的偏序关系意义下的Pareto最优集就是满足约束条件的Pareto最优集，从而在对种群中的个体进行评估或排序时，并不需要特别去关心个体是否可行，避免了罚函数选择参数的困难，尝试应用有限Markov链的有关理论证明了此进化算法的收敛性，用较复杂的Benchmark函数进行了大量的数值实验，测试结果表明新算法在解集分布的均匀性、多样性以及快速收敛性均较理想。     

粒子群优化ABC支持型QoS单播路由机制

设计了一种ABC支持型QoS单播路由机制,采用区间形式描述不精确用户QoS需求和边（链路）参数,引入用户满意度、边评价和精英解集,通过博弈分析,应用粒子群优化算法,寻找使用户和网络提供方效用达到或接近Nash均衡下Pareto最优的QoS单播路径。仿真结果表明,该机制是可行和有效的。     

住宅建筑方案优化设计研究与实现

文中将数学优化思想方法应用于建筑方案设计，具体介绍了算法数学模型的建立，确定了应用于住宅建筑优化算法的目标函数、设计向量和约束条件；同时，给出了一个基于模糊综合评判思想对方案进行评价和优选的方法，并较详细地阐述了计算机软件结构及其实现技术和方法。     

基于循环映射模型的概念设计自动化策略研究

建立了由主体特征和接口特征组成的功能特征模型,以及基于“需求域-功能域-原理解域循环映射”的概念设计模型;在此基础上提出了适用于计算机处理的概念设计与／或树形式化表达方法,探讨了相应的求解算法,开发了一个支持功能设计和功能求解的复合功能概念设计自动化原型系统,并以木材加工机械的概念设计为例进行了验证．     

基于遗传算法的方案智能优化设计

建立方案智能优化设计的过程模型，提出一种新的方案智能优化设计的求解方法模型：知识－分析－生成－评价－进化，研究了基于遗传算法的方案智能优化设计的关键技术，作为工程实例建立了起重机起升装置方案优化设计智能系统。     

大数据环境下高校移动学习平台的设计与实现

传统的教学方式正在发生变革,移动化学习越来越成为老师和学生进行教与学的一种新手段,尤其是智能手机的普及和大数据技术的发展。随着越来越多的学习者习惯于用移动设备进行学习,现有学习平台的局限性就越来越明显。该文以大数据为基础,设计了高校智慧移动学习平台解决方案。该平台主要实现对学习内容进行智能化推荐,文中主要对系统中的推荐理论模型进行详细介绍——建立主要的模糊推荐需求集合;建立高级的模糊推荐需求集;设计模糊推荐算法。平台可根据学习者动态的学习情况,智能推荐合适的学习内容,并将实时信息告知学习者,结果分析证明该平台可靠且易于使用。该方案对普通高校的教学具有一定的推动作用,为教学创新提供了新的参考。     

Conceptual design of a user-centric smart product-service system using self-organizing map

As an emerging IT-driven business paradigm, smart product-service system (Smart PSS), which offers not only the smart, connected product (SCP) but also its generated service as a solution bundle, has become a vital research topic. Many research efforts have been devoted to constructing the conceptual design framework by considering SCPs and services simultaneously. However, the following critical issues in Smart PSS conceptual design have not been well addressed: how to improve the solution of Smart PSS in the conceptual design stage to meet user emotional requirements. Aiming to fill the gap, this work proposes a conceptual design method for Smart PSS from the perspective of analyzing user-generated emotions/feelings. Specifically, the relevant traditional products are identified, and their public review data is used to analyze user emotions/feelings in user-product interaction. Interactive emotion board as a new design tool is presented to organize the user-generated emotions/feelings, associated design elements, and the potential design points of the initial solution. And the analytic hierarchy process (AHP) is utilized to evaluate the improved solution. To ensure the efficiency of the analysis process, the self-organizing map (SOM) algorithm is utilized in the process of clustering product samples and Kansei words. A case study of smart electric bicycle service system (SEBSS) design is used to demonstrate the performance of the proposed method. Based on the case study, the proposed approach appears effective in helping with Smart PSS conceptual design.     

A sharing-oriented service selection and scheduling approach for the optimization of resource utilization

We present a sharing-oriented service selection and scheduling approach capable of finding a trade-off between requirement satisfaction degree, service utilization rate and service sharing cost for limited quantities and capacities of available services. In traditional service selection approaches, each customer requirement is independently satisfied by optimally selecting a set of candidate service resources. However, in real-life service scenarios, it is usual for multiple customers to raise their requirements simultaneously, and available services need to be allocated between them. Especially, when available services are limited in both quantity and capacity, a traditional “first-come-first-serve” strategy would lead to a low service utilization rate, and some requirements cannot be satisfied at all (i.e., a low requirement satisfaction degree). Our approach makes use of the feature that some services can be shared by several customer requirements. Specifically, a virtualized service resource consisting of multiple candidate services is constructed and scheduled to satisfy multiple customer requirements simultaneously. Our approach searches for the global optimization on requirement satisfaction degree, service utilization rate, and service sharing cost. We build a mathematical model for this multi-objective optimization problem and propose a nested genetic algorithm mixed with a greedy strategy. Experiments in an ocean transportation service setting are conducted and our approach is compared with traditional approaches to validate its effectiveness.     

Set based robust design of mechanical systems using the quantifier constraint satisfaction algorithm

Embodiment design is an important phase of the design process where the initial design parameters and their feasible solution spaces with design configurations are decided for the design problem. This article presents a new approach of embodiment design space exploration of the product based on set based design with integration of robustness for the mechanical systems. The approach presented addresses the initial design phase of the mechanical systems design and provides a three step approach based on a formal expression syntax, transformation and evaluation engine and a computational algorithm for performing a domain search for sets of robust solutions for the product designs by taking into the account the variations and uncertainties related to the manufacturing process and material. The approach is based on the design domain exploration and reduction techniques. This is achieved by the utilization and integration of existential and universal quantifiers from the quantifier constraint satisfaction problem (QCSP) for the expression of the parameters and variables related to the product design and robustness. The quantifier notion has been used to develop the consistency check for the existence of a design solution and existence of a robust design solution. In order to compute the developed quantifier approach, an algorithm based on the transformation of the quantifier with interval arithmetic has also been developed. In order to demonstrate the capability of the developed approach, this article includes three examples of mechanical systems from earlier research works that apply the quantifier model and the resolution algorithm to successfully explore the design domain for robust solutions while taking into account different types of variations such as variations in mechanical/material properties, manufacturing variations or variations in geometric dimensions which may be of continuous or discrete type.     

基于用户功能需求的知识网的自动生成研究

研究了基于用户功能需求的知识网自动生成方法.首先,定义了知识网对用户需求的满意度关系及其运算,建立了知识网多重集运算表达式优化的模型;然后,基于改进的混合遗传算法,对知识网多重集表达式进行优化,给出了知识网自动生成的步骤;最后,通过算例对知识网自动生成方法进行说明和验证,表明了该方法的有效性和可行性.     

满足客户个性化需求的服务匹配算法

为应用Web Services实现个性化流程,提出了一种满足客户个性化需求的服务匹配方法.基于虚拟旅游服务平台,将不同客户的兴趣偏好转化为对应不同权值的非功能性属性. 根据对非功能性属性语义的规范化表示,通过对非功能性属性语义和约束的匹配,以及对非功能性属性满意度的综合评价,实现了更贴近于客户需求的个性化流程.模拟算例表明,该算法有效,为个性化流程提供了可参考的求解算法,弥补了基于静态功能性属性服务匹配的不足.