离散多种群入侵杂草优化算法求解柔性作业车间调度问题

针对柔性作业车间调度问题(FJSP)的特点,在基本入侵杂草优化算法原理的基础上,提出一种离散多种群入侵杂草优化算法.该算法引入多种群思想且在算法初期不进行种群交流,在各种群内采用交叉算子进行交流.当空间扩展时,采用自适应变异位数策略和领域搜索策略,提高了算法初期的全局搜索和后期的局部挖掘能力.在算法后期进行种群交流,提高了算法的收敛速度和寻优精度.将该算法用于柔性作业车间调度问题,且在解码时提出一种矩阵解码法.计算实例验证了所提出算法的有效性和优越性.     

基于改进NSGA-Ⅲ算法的多目标柔性作业车间调度

针对多目标柔性作业车间调度问题求解效率低的难题,提出了一种改进NSGA-Ⅲ(non-dominated sorting genetic algorithm-Ⅲ)调度优化算法。首先,建立了考虑直接能耗和间接能耗的多目标柔性作业车间调度模型;然后,结合两段式编码设计了一种混合分配策略,应用于种群的初始化,并通过进化算子确定子代种群的生成;最后,基于参考点的小生境选择策略,利用双层正交边界交叉方法生成一组预定的参考点,并根据种群熵值变化率设计自适应淘汰策略用于非支配精英存储策略。通过对11个作业车间调度问题算例进行改造,验证了改进算法求解多目标柔性作业车间调度问题具有较高的求解质量和求解效率。     

改进灰狼算法求解多目标柔性作业车间调度问题

柔性作业车间调度问题(Flexible Jobshop Scheduling Problem,FJSP)是经典的NP-hard(Nondeterministic Polynomial-time hard)问题,针对该复杂问题,需要建立一个多目标的数学模型,采用灰狼优化算法对柔性作业车间的加工完成时间、总耗能和总机器负荷这三个目标进行优化,以加工完成时间、总耗能和总机器负荷作为研究目标。灰狼优化算法(GWO)是一种具有较高的寻优精度和收敛速度的算法,在此基础上对灰狼优化算法的初始化种群进行改进,为了使灰狼算法适用于多目标问题,与非支配排序遗传算法结合,引入非支配排序与拥挤度的概念,用于灰狼算法对种群的更新。对柔性作业车间调度算例进行测试,结果表明改进的灰狼算法针对多目标柔性作业车间调度可以找到最优解,以较少的迭代次数找到最小加工时间、最小总耗能及最小总机器负荷,对车间调度问题进行了优化。     

基于AGV的管道加热器柔性作业车间调度方法研究

针对基于AGV约束的管道加热器柔性作业车间调度问题,以最小化最大完工时间和最小化车间总负载为目标,提出改进麻雀搜索算法求解调度方案;建立合理的编解码方式表示调度方案;为解决多目标优化问题,引入Patero排序;考虑麻雀搜索算法求解离散优化问题时无效解较多、易陷入局部最优等缺陷,提出引入交叉变异算子、设置精英种群、设计自适应种群比例因子等改进措施;根据标准算例数据及实际车间生产数据对算法可行性进行验证,结果表明改进算法可有效求解合理的调度方案,相比于车间原生产方案,生产效率提高19.6%,且有效降低了车间总负载。     

利用历史信息和限制算子求解MOFJSP

在绿色车间实际生产中,生产者要求在尽量短的时间内获得符合要求的多目标柔性作业车间的调度方案。提出一种使用个体历史信息和限制算子求解柔性作业车间优化调度问题的方法。该方法将多个优化目标分解为一组标量子问题,利用多目标进化算法优化子进行目标优化;在进化过程中,子代生成阶段使用历史信息,提高个体的改变量,加快收敛;在选择阶段,利用带有限制信息的稳定匹配选择策略选择多样性好的染色体种群作为下一次进化的父代种群,保证种群的多样性。实例仿真表明：相比已有算法,所提算法在效率、成本以及能效三个目标上分别提升0.8%、0.8%、2.5%,同时优于NSGA-II求解方案的1.4%、1.8%、4.8%。     

一种多尺度协同变异的萤火虫粒子群混合算法及在车间调度中的应用

车间调度对于制造企业提高生产效率、降低生产成本具有重要的作用,针对单一优化算法在解决调度优化问题时存在的不足,探索求解速度和求解质量的均衡,提出了一种多尺度协同变异的萤火虫粒子群混合算法;引入动态自适应策略把种群分为两组,对两组族群平行进化,在保持种群多样性的同时提高求解速度;引入多尺度协同变异算子,利用不同大小方差的自适应高斯变异机制使种群以尽量分散的变异尺度来搜索解空间,通过混沌初始化种群进一步提高算法的局部检索能力;将提出的算法应用于函数优化和流水车间调度问题求解,实验结果显示,算法在求解效率、精度方面优于对比算法,具有较好的性能和应用价值。     

批量生产柔性作业车间多目标精细化调度方法

提出了一种批量生产柔性作业车间多目标精细化调度方法。针对批量生产柔性作业车间多目标调度问题特点,建立了一类以完工时间最短和制造成本最低为优化目标的等量分批柔性作业车间调度多目标优化模型。提出了5种批量生产柔性作业车间精细化调度技术;设计了一种改进的NSGA II算法对模型进行求解。算法中引入面向对象技术处理复杂的实体逻辑关系,使用矩阵编码技术进行编码,采用分段交叉和分段变异的遗传算子实现遗传进化,应用上述5种精细化调度技术于解码过程以提高设备利用率。通过案例分析验证了该方法的有效性。     

基于改进双档案多目标进化算法的柔性作业车间批量流混排调度

针对柔性作业车间批量流调度问题,基于快速换模技术,考虑可变子批划分柔性、子批混排加工柔性、自动换模柔性和物料运输柔性,建立以最小化完工时间和加工子批总数为目标的混排调度优化模型,并提出一种改进双档案多目标进化算法以优化目标函数。基于进化算法框架,设计了基于超体积指标和基于改进帕累托支配的双档案筛选机制,以平衡种群的收敛性和多样性;针对批量流混排调度问题特征,在解码阶段提出正/逆解码和子批拆分左移策略,在邻域探索和全局搜索阶段分别设计子批划分和混排调度的自适应进化算子,以提高算法的全局搜索与局部搜索能力。基于不同规模算例,测试了提出算法与经典多目标算法的性能。实验结果表明,该算法在收敛性与多样性上具有明显优势。     

双资源批量生产柔性作业车间多目标调度方法

针对双资源批量生产柔性作业车间调度问题,提出了一种多目标精细化调度方法。针对双资源批量生产柔性作业车间多目标调度问题特点,建立了一类以制造成本最低和完工时间最短为优化目标的双资源等量分批柔性作业车间调度多目标优化模型;提出了5种双资源批量生产柔性作业车间精细化调度技术;针对模型提出并设计了一种改进的NSGA II算法。通过案例分析验证了该方法的有效性。     

求解区间柔性作业车间调度的多目标进化算法

针对不确定多目标柔性作业车间调度问题,将工序加工时间采用区间数表示,以区间最大完工时间和区间机器总负荷为优化目标,构建多目标区间柔性作业车间调度模型,并设计一种多目标进化优化算法对该模型进行求解.算法采用混合策略生成初始化种群,并采用贪婪插入法对染色体进行解码,通过基于可能度的占优关系评价个体性能,将区间目标归一化结合拥挤距离反映优化解的分布情况.实验结果验证了所提出算法的有效性.     

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.