基于规则的动态工作流建模方法的研究与设计

现代企业流程所固有的多变性和灵活性,凸显了工作流在处理动态不确定因素方面的不足。针对这一情况,提出了一种基于ECA（event—condition—action）规则和活动选取一组合规则的动态工作流模型。该模型采用柔性活动对流程中的不确定因素进行了封装,用活动选取一组合规则来约束柔性活动的具体化过程,并设计了一种高效的活动自动选取一组合算法,来实现柔性活动的具体化。     

工作流时序约束模型分析与验证方法

为了解决工作流时间建模与时序一致性验证问题,以时序逻辑和模型检查为基础,提出了一种工作流时间建模与时序一致性验证方法.该方法用一阶逻辑描述工作流模型及其时间信息,用时序逻辑描述工作流的时序约束,用模型检查算法对时序约束进行验证与分析.该方法不是针对某一种时序约束提出来的,而是能够验证任何用时序逻辑描述的工作流时序约束.该方法还能够对未通过验证的时序约束提供工作流运行实例作为反例,帮助用户定位模型的问题.以一个工作流时间建模和时序一致性验证的实例证实了所提出方法的有效性.     

基于动态工作流的临床路径信息系统架构研究

针对临床路径中的变异性,提出了基于动态工作流的临床路径信息系统,并给出系统的整体架构。在工作流建模时,采用动态工作流技术来约束柔性活动的具体化过程,及时处理临床路径中出现的变异。     

基于工作流的知识流建模与控制

知识在多个参与者之间的产生、传播与应用称为知识流.在知识密集型组织中,对业务过程的控制和对知识资产的管理具有紧密的依赖关系.工作流管理是实现业务过程控制的重要技术.当前的工作流过程元模型不支持对知识管理机制的表示.为此,提出了一个扩展的工作流过程元模型,以支持业务过程控制与知识管理的集成.在此基础上,对知识流的建模与控制进行了深入的研究.提出了一种知识流建模方法,通过5类知识流单元对知识传递与重用、人员协作与交流进行表示.针对知识流中的动态因素,研究了基于资源约束、知识需求变化和时间约束的知识流控制方法,以实现自适应的知识流控制,并给出了有关算法.为工作流技术与知识管理技术的有效结合提供了一个有益的途径.     

柔性工作流管理系统建模与实现

本文分析了工作流管理系统柔性方面的具体要求,提出了一个柔性工作流系统的体系结构和工作流柔性建模方法。该方法在模型定义中加入过程元素,通过将活动分为静态过程和动态过程较好的满足了工作流系统的柔性要求。     

基于动态结构的柔性工作流建模方法研究

柔性工作流能够快速灵活地适应企业业务流程的动态变化。在分析柔性工作流产生的原因和柔性工作流特性的基础上,详细描述了基于动态结构的柔性工作流的组成及其表示方法,提出了一种柔性工作流建模方法,结合基于Web的客户服务系统,给出了该柔性工作流建模方法的实例。     

基于交互学习的柔性工作流

当前工作流系统普遍缺乏柔性，导致适应性和实用性较差．在工作流网(WF—Net)的基础上，增加了柔性场所和柔性迁移，提出了一种柔性工作流网(FWF—Net)的建模语言并对正确性进行了分析；同时在工作流系统中增加了建模和执行的交互学习机制，给出了学习的算法，使工作流系统从建模和执行都具有良好的柔性和适应性，同时降低复杂性．通过实验表明，不但能够实现柔性工作流系统，而且支持个性化的流程管理．     

基于动态装配模式的柔性工作流管理系统

针对传统工作流管理系统复杂建模的不足，提出了一个适用于复杂系统中关键业务开发的基于关系结构的动态装配的柔性工作流管理系统的框架结构。文中结合法制系统的背景讨论了该框架的模块，以及模块间的引擎调度和柔性控制，并给出了设计和实现。     

柔性工作流逻辑建模及其合理性研究

随着市场竞争的加剧和企业对提高工作效率的迫切需要,柔性工作流成为研究的热点。为了解决工作流逻辑模型的建立以及动态修改问题,提出了一种以面向对象编程思想为工具,以模型中任务依赖关系为主要研究对象的柔性工作流逻辑网(WL_net)建模方法。通过对存在缺陷的工作流逻辑模型路由结构进行分析,找出了一种模型合理性验证算法。     

动态工作流挖掘模型及算法研究

工作流挖掘是工作流再设计与分析的一项关键技术,目的在于从企业已有信息系统的日志记录中提取与实际应用相关的业务流程,从而提高工作流建模的客观性。从实际应用的角度出发,提出基于动态工作流网的挖掘模型,并设计了可行的算法。该算法从零日志开始,在工作流执行期间柔性地构建工作流模型和生成日志记录,动态生成工作流网,在很大程度上解决了常规挖掘方法在挖掘复杂结构效率低、准确性差、依赖完整的日志记录和不支持柔性工作流等方面的问题。算法的实用性在实际应用系统中得到了很好的证明。     

A novel flexible activity refinement approach for improving workflow process flexibility

Flexible activity refinement plays an important role in improving process flexibility and addressing uncertainties of business processes. However, it is still a challenge to refine flexible activities, and the existing researches on flexible activity refinement such as the refinement principles and methods, and their combination with factors such as constraints and contexts is still lacking. Aiming at this, a novel dynamic refinement approach for flexible activities is proposed, which combines both vertical decomposition and horizontal extension refinements, with the impact of constraints and contexts considered. In particular, we summarize five typical refinement categories, and present a set of activity refinement rules based on them. Furthermore, the decomposition refinement, including the activity decomposition principles, the related rules for trigger event delivering and execution condition transferring is discussed in detail. The extension refinement, which realizes the horizontal refinement, can be integrated with other kinds of refinement and uses constraints to specify activity selection, activity temporal relationships, etc. Then, a tree-like activity refinement graph (ARG) is proposed to represent the refinement process, based on which the refinement cost and refinement degree can be computed to benefit the finding of the potential optimal refinement path. As a further implementation of the proposed refinement approach, a general refinement algorithm is described. Finally, a case study of urolithiasis therapy process and its application are given, and the results indicate the effectiveness of our proposals.     

Improving constrained clustering with active query selection

In this article, we address the problem of automatic constraint selection to improve the performance of constraint-based clustering algorithms. To this aim we propose a novel active learning algorithm that relies on a k-nearest neighbors graph and a new constraint utility function to generate queries to the human expert. This mechanism is paired with propagation and refinement processes that limit the number of constraint candidates and introduce a minimal diversity in the proposed constraints. Existing constraint selection heuristics are based on a random selection or on a min–max criterion and thus are either inefficient or more adapted to spherical clusters. Contrary to these approaches, our method is designed to be beneficial for all constraint-based clustering algorithms. Comparative experiments conducted on real datasets and with two distinct representative constraint-based clustering algorithms show that our approach significantly improves clustering quality while minimizing the number of human expert solicitations.     

Controlled violation of temporal process constraints – Models,algorithms and results

While there has been much work on modeling and analysis of temporal constraints in workflows in the context of many real-world applications, there has not been much work on managing violations of temporal constraints. In real-time workflows, such as in medical processes and emergency situations, and also in logistics, finance and in other business processes with deadlines some violations are unavoidable. Here we introduce the notion of controlled violations as the ability to monitor a running process and develop an approach based on constraint satisfaction to determine the best schedule for its completion in a way so as to minimize the total penalty from the violations. The violations are evaluated in terms of metrics like number of violations, delay in process completion, and penalty of weighted violations. We also relate our work to the concept of controllability in literature and show how it can be checked using our method. Finally, we analyze the properties of our approach and also offer a proposal for implementation.     

Contract-collaboration network method for modeling manufacturing resource control workflows

This paper presents contract-collaboration network (CC-Net) method that is developed to model manufacturing resource control workflows. The CC-Net is an object-oriented class diagram. It depicts the contract-collaboration relationships among the classes in a manufacturing system, with constraints. The CC-Net method uses a primitive modeling block called collaboration module by which the CC-Net is established systematically. This idea is very similar to that of the Lego® block toy. Unlike most workflow modeling methods, the CC-Net method views workflow modeling as a constraint satisfaction process. That is, describing the set of constraint recovery rules corresponding to the constraint violations is regarded as workflow modeling. The obtained set of workflow rules is free from process deadlock and considers all the events of triggering the workflow. We explore the use of the CC-Net method for the workflow modeling of a flexible manufacturing system.     

基于Petri网的工作流时间动态预测及验证

目前,工作流管理系统不能有效的处理时间管理问题,为了动态预测活动发生的时间间隔,验证时间的一致性,预知潜在的时间冲突,首先建立基于时间Petri网的扩展工作流网(XTWF-net),然后根据工作流管理联盟规定的几种基本结构推导出时间预测规则,并采用面向对象技术实现了预测算法,最后给出了动态验证的方法和决策策略.     

Efficient Sequence Alignment with Side-Constraints by Cluster Tree Elimination

Aligning DNA and protein sequences is a core technique in molecular biology. Often, it is desirable to include partial prior knowledge and conditions in an alignment. Going beyond prior work, we aim at the integration of such side constraints in free combination into alignment algorithms. The most common and successful technique for efficient alignment algorithms is dynamic programming (DP). However, a weakness of DP is that one cannot include additional constraints without specifically tailoring a new DP algorithm. Here, we discuss a declarative approach that is based on constraint techniques and show how it can be extended by formulating additional knowledge as constraints. We take special care to obtain the efficiency of DP for sequence alignment. This is achieved by careful modeling and applying proper solving strategies. Finally, we apply our method to the scanning for RNA motifs in large sequences. This case study demonstrates how the new approach can be used in real biological problems. A prototypic implementation of the method is available at .     

基于时间约束Petri网的工作流动态一致性检验

工作流系统中的时间管理是工作流建模和分析的重要组成部分。支持动态修改是人们在实际应用中对工作流系统提出的新要求。文中在基于时间约束的Petri网模型基础上,根据时间约束推理规则,提出一种动态修改时间约束时检验工作流一致性的方法,从而丰富了工作流的时间管理功能。     

基于PBIL算法的高校自动排考系统

提出了一种基于PBIL的高校自动排考算法,重点论述了如何优化目标函数与排考约束条件之间的关系,并对PBIL基因选择算法提出了改进。通过实际的测试应用,基于PBIL算法的自动排考系统能够较好地满足学分制下的自动排考需求,对附加约束条件具有较强的适应性,能够满足各个学校的不同排考需求。