多目标多约束应急物资调度优化的仿真研究

研究突发事件应急物资调度优化问题,应急物资具有多目标、多约束、动态性特性,传统粒子群算法存在"早熟"缺陷,无法获得最优调度方案,为解决上述问题,提出一种采用混沌粒子群优化算法的突发事件应急物资调度优化模型。首先建立应急物资调度优化数学模型,并确立目标函数,然后采用混沌粒子群算法对其进行求解,最后采用仿真测试算法的有效性和可行性。仿真结果表明,混沌粒子群算法克服了传统优化方法易陷入局部最优的缺陷,在保证应急时间最短的前提下,运输总成本最低本。     

基于学习效应的应急救援车辆调度问题综述

突发灾害事件情景下,合理的应急救援车辆路径选择是减少人员、财产损失的有效有效途径,通过综述国内外学者针对应急救援车辆路径优化问题模型及求解算法的研究,结合突发灾害事件急迫性的特点,分析了求解模型的不合理之处以及求解算法的缺陷。提出学习效应在应急救援车辆路径优化问题中的应用价值,分析了当下应急救援研究方向。最后,结合目前应急救援的缺陷,展望了今后应急救援车辆路径优化问题的发展趋势。     

自适应混沌蚁群算法的粮食应急路径优化研究

针对风险管理下的粮食应急路径优化问题,将"运输风险最小"和"运输时间最小"作为目标,建立相应的优化模型。利用"最大最小蚂蚁系统"进行求解,为避免过早陷入局部最优,提出自适应混沌蚁群优化算法。该算法利用有效解相似度来判断蚁群当前状态,根据情况对信息素进行全局更新和混沌扰动,可以有效地提高最优解的精度。实验表明该算法优于传统的演化算法,较好地解决了粮食应急运输路径优化问题。     

基于萤火虫算法的应急救援车辆调度

针对突发灾害事件情景下交通路网容量限定的特点,引用BRP路阻函数求解各路段车辆行驶时间,建立救援路径最短和车辆行驶时间最短双目标车辆调度模型;设计改进离散的萤火虫算法,构建算例对模型求解,求解结果与遗传算法的求解结果进行对比,验证了该算法的可行性和能更好的满足应急救援车辆调度的需要.     

混合粒子群算法在ETV调度优化中的应用

为了提高机场货运区(Elevating Transfer Vehicle,ETV)转运效率,建立以最小化任务集调度时间为优化目标的调度模型,提出一种混合的粒子群算法对ETV调度问题求解。算法对加速因子采取动态的自适应调整策略;采用混沌序列替代标准粒子群中的随机数;建立平均粒距、适应度方差和汉明距离相结合的早熟判断机制并采用混沌算子扰动微粒的位置来跳出局部最优。通过实例验证和遗传算法、模拟退火等经典的优化算法以及非线性学习因子粒子群、混沌粒子群等改进的粒子群算法相比,该算法在ETV调度最优序列的求解中收敛速度快,全局寻优能力强,稳定性好;和传统的链式调度算法相比,平均调度任务时间减少了15.6%,较好地解决了ETV转运效率低的问题。     

考虑备灾的双层规划应急资源调度选址—路径优化模型与算法

备灾措施可以为救灾做准备,为确保灾后应急物资可以及时高效地到达灾区,提出了考虑备灾的双层规划应急资源调度选址—路径优化模型,上层规划以供应站建设和运营总成本最低为目标,而下层规划以配送路径成本最小化为目标.设计了一种改进的双层樽海鞘遗传算法求解该问题,结合迭代划分的概念更新领导者位置,采用自然指数惯性权值策略修正控制因子,利用混沌映射更新追随者位置,采用田口分析方法获取参数合理取值.最后,通过使用双层樽海鞘遗传算法与遗传粒子群混合算法、粒子群优化算法、免疫优化算法对OR-Library中的LRP(location-routing problem,LRP)数据集进行求解和对比分析,验证了所提模型和算法的可行性和有效性.     

混沌扰动模拟退火蚁群算法低碳物流路径优化

低碳物流是目前物流配送领域的热点研究课题,也是群体智能优化算法的重要应用方向。针对物流配送中碳排放的度量方法,以VRP问题为基本模型,以碳排放成本为目标函数,建立了低碳物流配送路径优化模型。为了避免基本蚁群算法出现停滞及早熟现象,提出了带混沌扰动的模拟退火蚁群算法来求解低碳物流配送路径优化模型。该算法将混沌系统及模拟退火机制引入基本蚁群算法,避免了算法陷入局部最优,增强了全局搜索能力,提高了求解效率。通过实验仿真及对比分析可知,带混沌扰动的模拟退火蚁群算法的求解结果明显优于基本蚁群算法,表明了该算法的有效性和合理性。     

基于蚁群算法的粮食应急调度问题研究

为解决粮食应急调度问题,建立一个适合多应急点、多出救点的多目标优化模型。将“应急开始时间最早”和“出救点数目最少”作为优化目标,考虑每个应急点的紧急重要程度和粮食自身的消耗特点,引入相应因子。应用蚁群算法对模型进行求解,给出算法求解的具体步骤。数值算例表明,该模型可提高粮食的应急调度效率。     

混沌粒子群优化算法研究

利用混沌运动的遍历性、随机性和规律性等特点,提出一种求解优化问题的混沌粒子群优化(CPSO)算法.该算法的基本思想是采用混沌初始化进行改善个体质量和利用混沌扰动避免搜索过程陷入局部极值.典型复杂函数优化仿真结果表明该方法是一种较简单有效的算法.     

基于鲸鱼群优化算法的带Sigmoid满意度应急车辆调度问题

针对突发大规模灾害事件下受灾点严重程度不同的特点,引入Sigmoid时间满意函数评价救援效果,建立平均时间满意度最大与救援路径最短双目标调度模型.设计了基于混沌序列搜索算子的混沌鲸鱼群算法,通过构建三组不同规模的实验案例对模型进行求解,并将所得结果与模拟退火算法和基本鲸鱼群算法进行比较.实验表明,在处理较小规模车辆调度情况下,三种算法处理效果差距不明显,随着求解规模增大,混沌鲸鱼群算法对解决所提问题具有更好的效果,是一种优化应急车辆的有效方法.     

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.