基于正交设计的自适应ε占优MOEA/D算法研究

MOEA/D是一种简单、高效的多目标优化算法,但在更新子问题时,会丢失部分优良个体,降低算法的收敛速度。针对上述不足,提出一种基于正交设计的自适应ε占优算法。新算法改进如下:(1)采用正交试验设计和连续空间量化初始化种群,使初始化群体能均匀分布;(2)设计一种自适应调整松弛变量改进的ε占优机制,并用它来更新Archive种群保存非劣解;(3)将精英策略引入到MOEA/D中,加快收敛速度。实验结果表明新算法较好地改善了MOEA/D算法的收敛性以及非劣解的分布性。     

基于变异算子和邻域值自适应的MOEA/D算法

基于分解的多目标进化算法（MOEA/D）在解决多目标问题时，具有简单有效的特点。但多数MOEA/D采用固定的控制参数，导致全局搜索能力差，难以平衡收敛性和多样性。针对以上问题提出一种基于变异算子和邻域值自适应的多目标优化算法。该算法根据种群中个体适应度值的分散或集中程度进行判断，并据此对变异算子进行自适应的调节，从而增强算法的全局搜索能力；根据进化所处的阶段以及个体适应度值的集中程度，自适应地调节邻域值大小，保证每个个体在不同的进化代数都有一个邻域值大小；在子问题邻域中，统计子问题对应个体的被支配数，通过判断被支配数是否超过设定的上限，来决定是否将Pareto支配关系也作为邻域内判断个体好坏的准则之一。将提出的算法与传统的MOEA/D在标准测试问题上进行对比。实验结果表明，提出的算法求得的解集具有更好的收敛性和多样性，在求解性能上具有一定的优势。     

全局替换的自适应权重调整MOEA/D

当多目标问题的帕累托前沿形状较为复杂时,基于分解的多目标进化算法MOEA/D的解的均匀性将受到很大的影响. MOEA/D利用相邻子问题的信息来优化,但早期因为种群中的个体与子问题的关联是随机分配的,仅在邻居间更新会浪费优秀解的信息,影响收敛速度.针对这些问题,本文提出一种MOEA/D的改进算法(MOEA/DGUAW).该算法使用种群全局更新的策略,来提高收敛速度;使用自适应调整权重向量的策略来获得更均匀分布的解集.将MOEA/D-GUAW算法与现有的MOEA/D, MOEA/D-AWA, RVEA和NSGA-III算法在10个广泛应用的测试问题上进行了实验比较.实验结果表明,提出的算法在大部分问题上,反转世代距离评价指标IGD优于其他算法,收敛速度也快于其他算法.     

基于自适应邻域策略的改进型MOEA/D算法

为避免传统MOEA/D算法使用固定领域规模易造成种群进化效率降低的情况,提出一种基于自适应邻域策略的改进算法。设计一种能够反映子问题进化幅度和种群进化状态的判断机制。针对进化过程中的收敛性和分布性需求,提出基于进化状态判断的自适应邻域策略,从而根据种群和子问题的进化状态设定不同的邻域规模。使用WFG系列测试函数进行实验,结果表明,该算法能有效平衡进化过程中种群的收敛性与分布性,提高解集的整体性能。     

随机扰动不同种群变异策略的多目标进化算法

为了提高多目标优化问题非支配解集的收敛性和多样性,解决算法后期易陷入局部最优的问题,根据不同差分进化策略特点,添加随机扰动,基于改进切比雪夫机制提出了一种自适应差分进化策略的分解多目标进化算法（MOEA/D-ADE-levy）。首先使用混合水平正交实验产生均匀权重向量并应用于改进切比雪夫机制分解子问题得到均匀分布的初始种群;其次将种群分为优秀个体、中间个体和较差个体,对不同个体采用不同的变异策略,对变异因子F和交叉概率CR采用自适应机制,提高非支配解集的收敛性和多样性;最后对陷入局部最优的解集增加levy随机扰动,增大其全局搜索的能力,跳出局部最优。采用DTLZ测试函数验证算法有效性,将所提算法与NSGA2、NSGA3、MOEA\D、MOEA\D-DE等常用算法进行比较,使用GD和IGD评价指标对算法进行多样性和收敛性分析,实验结果表明,该算法在收敛性和多样性方面得到了改进与提高,能得到更优的Pareto解集。     

改进MOEA/D算法的异构网络接入控制

为改善异构无线网络的业务接入质量,建立异构无线网络的多目标优化数学模型,利用权重向量与个体的匹配优化和自适应领域的策略对MOEA/D算法进行改进,提升种群的多样性和算法收敛性,还使Pareto最优解的分布更加均匀.通过在8个多目标函数上进行测试,得到的IGD均值和标准差明显优于其它3种比较算法,验证了改进策略的有效性和...     

基于差异化邻域策略的分解多目标进化算法*

子问题邻域对基于分解的多目标进化算法性能影响较大.当邻域过大时,种群繁殖产生的新解偏离Pareto解集,在更新子问题时,新解与邻域内旧解的比较次数增多,算法的计算复杂度增加;当邻域过小时,算法容易陷入局部最优.为了解决上述问题,文中提出基于差异化邻域策略的分解多目标进化算法(MOEA/D-DN),通过分析不同大小的邻域对算法性能的影响,选择合适的参数.并根据每个子问题的权重向量与中心向量的偏角,为各子问题设置不同大小的邻域,合理分配算法资源,提高算法搜索全局最优解的速率.在2维ZDT系列和3维、5维DTLZ系列测试函数上的实验表明,MOEA/D-DN 的收敛速度与收敛性能均有明显提高,算法的计算资源分配更合理,所获解集整体质量更优.     

基于邻域和变异算子组合优化的MOEA/D算法

考虑到在基于分解的多目标进化算法(MOEA/D)中,邻域大小与变异算子类型对算法进化过程中的探索模式有不同的影响,提出优化的MOEA/D算法。4种不同大小的邻域范围和4个特性不同的变异策略两两组合构成候选池,利用负反馈原则,在进化过程中以较高概率从候选池中选择表现更优的组合。实验结果表明,该算法鲁棒性较强,在保证收敛性的同时具有较好的多样性。     

一种基于偶图匹配的多目标分解进化算法

针对基于分解的多目标进化(MOEA/D)算法在选择下一代解时未考虑解和子问题之间的相对距离,可能导致算法得到的最终解多样性较差的问题,提出一种基于偶图匹配的多目标分解进化(MOEA/D-BM)算法.所提算法利用偶图匹配模型对解和子问题的相互关系进行建模,在选择下一代解的同时,考虑收敛性和多样性,以提高算法性能.通过与其他3种经典的多目标分解进化算法在多个测试函数上进行实验,验证了所提出算法的有效性.     

改进MOEA/D算法求解多目标模糊柔性车间调度问题

针对模糊柔性作业车间调度问题中关于求解多目标优化的研究中,利用模糊数表示相关参数,以最小化最大完工时间、总机器负载和最大机器负载为优化目标,提出一种改进MOEA/D算法的权重向量和初始化种群,以优化全局更新配对策略的多目标分解进化算法（I-MOEA/D）,以提高算法寻优能力。与MOEA/D、NSGA-Ⅱ和NSGA-Ⅲ算法相比,该方法优于其他算法,同时引入企业工程实例进行分析,证明I-MOEA/D算法具备良好的收敛性和分布性。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.