教与同伴学习粒子群算法求解多目标柔性作业车间调度问题

针对多目标柔性作业车间调度问题,提出了带Pareto非支配解集的教与同伴学习粒子群算法。首先,以工件的最大完工时间、最大机器负荷和所有机器总负荷为优化目标建立了多目标柔性作业车间调度模型。然后,该算法结合多目标Pareto方法和教与同伴学习粒子群算法,采用快速非支配排序算法产生初始Pareto非支配解集,用提取Pareto支配层程序更新Pareto非支配解集,同时采用混合分派规则产生初始种群,采用开口向上抛物线递减的惯性权重选择策略提高算法的收敛速度。最后,对3个Benchmark算例进行仿真实验。理论分析和仿真表明,与带向导性局部搜索的多目标进化算法(MOEA-GLS)和带局部搜索的控制遗传算法(AL-CGA)相比,对于相同的测试实例,该算法能产生更多更好的Pareto非支配解;在计算时间方面,该算法要小于带向导性局部搜索的多目标进化算法。实验结果表明该算法可以有效解决多目标柔性作业车间调度问题。     

改进多目标进化算法求解柔性作业车间调度问题

针对加工时间为模糊数的柔性作业车间调度问题,考虑最小化模糊最大完工时间、模糊机器总负荷、模糊关键机器负荷为优化目标,提出一种有效求解该类优化问题的多目标进化算法。算法采用一种混合不同机器分配和工序排序策略的方法产生初始种群,并采用插入空隙法对染色体进行解码。定义一种新的基于可能度的个体支配关系和一种基于决策空间的拥挤算子,并将所提支配关系和拥挤算子运用于快速非支配排序。接着,提出一种基于移动模糊关键工序的局部搜索策略对种群中的优势个体进行局部搜索。通过试验研究关键参数对算法性能的影响并将所提算法与3种不同的优化算法作对比。结果表明,所提算法能够比其它算法更有效解决多目标模糊柔性作业车间调度优化问题。     

改进的基于分解的多目标进化算法求解双目标模糊柔性作业车间调度问题

针对同时考虑最大模糊完工时间和总模糊机器负载的双目标模糊柔性作业车间调度问题(BFFJSP),本文提出了一种改进的基于分解的多目标进化算法(IMOEA/D),同时最优化最大模糊完工时间和总模糊机器负载,其主要特点是:1)采用3种初始化种群的策略; 2)提出了非支配解优先策略; 3)设计了结合5种局部搜索策略的变邻域搜索; 4)提出了计数器策略预防陷入局部解.运用大量实例进行了算法策略分析和对比实验,仿真结果表明, IMOEA/D在求解BFFJSP上具有更优性能.     

柔性作业车间调度问题的多目标优化算法

柔性作业车间调度问题具有解集多样化与解空间复杂的特点,传统多目标优化算法求解时容易陷入局部最优且丢失解的多样性。在建立以最大完工时间、最大能耗、机器总负荷为优化目标的柔性作业车间调度模型的情况下,提出一种改进的非支配排序遗传算法（Improved Non-dominated Sorting Genetic Algorithm II, INSGA-II）求解该模型。INSGA-II算法先将随机式初始化与启发式初始化方法混合,提高种群多样性;然后对工序部分与机器部分采用针对性的交叉、变异策略,提高算法全局搜索能力;最后设计自适应的交叉、变异算子以兼顾算法的全局收敛与局部寻优能力。在mk01～mk07标准数据集上的实验结果显示INSGA-II算法有着更优的算法收敛性与解集多样性。     

改进人工蜂群算法求解分布式柔性作业车间调度问题

针对分布式柔性作业车间调度问题的特点,提出一种改进人工蜂群算法.首先,建立以最小化最大完工时间为优化目标的分布式柔性作业车间调度优化模型;然后,改进基本人工蜂群算法以使其适用于求解分布式柔性作业车间调度问题,具体的改进包括设计一种包含三维向量的编码方案,结合问题特点针对性地设计多种策略用于种群初始化,在雇佣蜂改良搜索操作中设计多种有效的进化操作算子,并在跟随蜂搜索操作中引入基于关键路径的局部搜索算子以提升算法的局部搜索能力;最后,利用扩展柔性作业车间通用测试集得到的测试数据设计实验验证算法性能,使用正交试验法优化算法参数设置.仿真实验结果表明,改进后的人工蜂群算法能有效求解分布式柔性作业车间调度问题.     

改进松鼠搜索算法求解分布式节能柔性调度

为了优化同时考虑最大完工时间和机器能耗的双目标分布式柔性作业车间调度问题,提出了一种改进的多目标松鼠搜索算法。引入了基于升序排列规则的转换机制,实现了松鼠位置向量与调度解之间的转换,并针对机器空闲时间设计了从半主动到主动的解码策略。针对不同优化目标设计了三种种群初始化策略。同时提出了动态捕食者策略来更好地协调算法的全局探索和局部开发能力。设计了四种领域搜索策略用于增加种群多样。20个实例上的实验结果验证了改进后的算法求得解的质量和多样性更好,从而证明了其可有效求解分布式节能柔性调度问题。     

考虑时间与能耗约束的柔性作业车间调度优化

随着能源价格日益上涨以及国家节能减排措施的不断推进,制造业正朝着绿色生产方向转型。针对受调整时间和能耗约束的柔性作业车间调度问题,建立以最大完工时间、总调整时间和总能耗为目标的数学模型。设计改进的NSGA-Ⅱ与禁忌搜索结合的多目标混合算法（MOGATS）进行求解。算法设计三种初始化规则保证初始解的质量和多样性。为提高算法搜索效果,将Pareto等级引入交叉算子中,并在变异算子中加入模拟退火算法提升算法的局部搜索能力。最后,在Pareto前沿中找到各个目标的最优个体作为初始解,进行禁忌搜索以提高解的质量。通过与其他算法的实验结果进行对比,验证MOGATS算法能够有效求解考虑机器调整的柔性作业车间多目标问题。     

考虑装卸的柔性作业车间双资源调度问题

针对“研产混线”中各类制造资源利用率低、非加工时间过长、调度难度大的问题,以生产中最紧缺的夹具资源为例,提出考虑装卸的柔性作业车间双资源调度问题.首先,以最小化完工时间和准结时间为目标建立该问题的数学优化模型;然后,设计快速非支配排序遗传算法对问题进行求解,根据问题特性综合考虑两个目标并设计降准解码算法,随机从交叉算子池和变异算子池中选择算子进行操作,根据非支配等级和拥挤度选择进入下一代的个体;最后,通过数值实验表明,针对考虑装卸的柔性作业车间双资源调度问题,所提出算法能够有效求解该问题,保证完工时间的同时降低准结时间.     

基于Q-learning算法解决多目标柔性作业车间调度问题

近几十年来，柔性作业车间调度问题由于其不确定性和复杂度引起了许多学者的关注。易陷入局部最优一直是元启发式算法解决柔性作业车间调度问题的不足之处，对此提出了一种改进的Q-learning强化学习算法，该改进算法设计并定义了状态空间和动作集，并通过随机生成可行的工序编码，在随机贪婪策略下选择合适的加工机器形成对应可行的机器编码，以最大完工时间和总能耗的多目标优化函数为可行解优劣的衡量标准。最后将所提算法模型使用车间调度问题的标准算例进行了验证，实验结果说明了所提算法的有效性，提升了解决多目标柔性作业车间问题的精度。     

变邻域杂草算法在多目标柔性作业车间调度中的应用*

针对最小化最大完工时间、总机床负荷最小及最大负载最小的多目标柔性作业车间调度问题,提出了变邻域杂草算法。首先,基于随机键编码方式,构造单链杂草,实现了杂草空间到调度空间的映射。其次,迭代后期执行变邻域搜索,对精英杂草局部深入挖掘,并通过反解码过程将调度空间的优良解反馈回杂草空间。对比实验表明,变邻域杂草算法在求解多目标基准问题时,非劣解集中解的数量和质量有一定优势。变邻域杂草算法是求解多目标柔性作业车间调度问题的有效方法。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and     

Editorial:Brain-machine interface(BMI) and cyborg intelligence

正Brain-machine interfaces(BMIs)aim at building a direct communication pathway between the brain and an external device,and represent an area of research where significant progress has been made during the past decade.Based on BMIs,mind information can be read out by neural signals to control     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate     

SCIENCE CHINA Information Sciences SUBJECT INDEX TO VOLUME 57(2014)

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Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate