基于变邻域下降的列车运行时刻调整算法

高速铁路区间失效可能严重影响列车正常运行,区间失效后调度员需要及时调整列车运行时刻.本文主要针对区间失效后不改变列车顺序下的时刻调整问题进行研究,建立了以所有列车在各站晚点时间之和为目标的列车运行调整模型,模型中各约束条件保证列车安全运行.针对目前常见的获取最优解或次优解需花费较长时间的问题,提出一种基于变邻域下降算法的多阶段变邻域下降算法.算法的第一、第二阶段使用变邻域下降算法结合禁忌表快速确定哪些列车经过调整后的时刻能与图定时刻相等,第三阶段则调整未恢复到图定时刻的列车.最后,以西成客运专线与某日的列车时刻数据为算例,求解多种区间失效场景下的列车运行时刻调整方案验证算法的有效性与实时性.     

Transformer-Based Macroscopic Regulation for High-Speed Railway Timetable Rescheduling

Unexpected delays in train operations can cause a cascade of negative consequences in a high-speed railway system. In such cases, train timetables need to be rescheduled. However, timely and efficient train timetable rescheduling is still a challenging problem due to its modeling difficulties and low optimization efficiency. This paper presents a Transformer-based macroscopic regulation approach which consists of two stages including Transformer-based modeling and policy-based decision-making. Firstly, the relationship between various train schedules and operations is described by creating a macroscopic model with the Transformer, providing the better understanding of overall operation in the high-speed railway system. Then, a policy-based approach is used to solve a continuous decision problem after macro-modeling for fast convergence. Extensive experiments on various delay scenarios are conducted. The results demonstrate the effectiveness of the proposed method in comparison to other popular methods.     

基于动态约束满足的炼钢连铸重调度算法

针对转炉出钢延迟的炼钢连铸重调度问题,以开工时间、加工时间以及加工机器的差异度和同一炉次相邻设备间的等待时间的差异化最小为目标建立了动态约束满足模型,提出了基于约束满足和断浇修复的重调度算法。算法通过变量和值选择规则依次对变量赋值,利用冲突识别与解消规则识别赋值过程中产生的冲突并予以解消冲突;在形成的准可行调度中,利用断浇修复启发式规则修复连铸机的断浇现象。仿真实验模拟了3组均匀分布随机产生的延迟时间量,所得目标值分别为0.15,0.28和0.51。结果表明延迟时间量的大小对目标函数值有一定影响,所提算法能够最大限度地满足生产的实时性和稳定性的需求。     

A Constraint-Based Approach to Assigning System Components to Tasks

In multi-component systems, individual components must be assigned to the tasks that they are to perform. In many applications, there are several possible task decompositions that could be used to achieve the task, and there are limited resources available throughout the system. We present a technique for making task assignments under these conditions. Constraint satisfaction is used to assign components to particular tasks. Heuristics suggest a task decomposition for which an assignment can be found efficiently. We have applied our technique to the problem of task assignment in systems of underwater robots and instrument platforms working together to collect data in the ocean.     

Constraint-Based Facial Animation

Constraints have been traditionally used for computer animation applications to define side conditions for generating synthesized motion according to a standard, usually physically realistic, set of motion equations. The case of facial animation is very different, as no set of motion equations for facial expressions is available. In this paper we discuss a facial animation editor, which uses numerical constraints for two roles: to declare the mimic repertoire of synthetic faces and other requirements a facial animation has to meet, and to aid the animator in the process of composing a specific animation fulfilling the requirements. The editor is thus also a ``motion sculpturing' tool, which lifts the task of creating facial animation from the control data manipulation level to the conceptual design level. The major aid of the editor is to repair inconsistencies due to changes made by the user, and revise changes for which no good repair is possible. Also, reuse of constrained animations, especially expressions, is supported. The main machinery behind these services is interval propagation, which, if using certain type of linear inequalities to express the character- as well as the animation-specific requirements, can produce quickly the interval of feasible values for each control variable. If a solution (usually, repair) has to be produced, it is generated by selecting the best one from a restricted set of acceptable solutions, based on user-defined or automatically generated criteria for the choices.     

光突发交换网络中的重调度算法

介绍了光突发交换（OBS）网络,在现有算法LAUC_VF的基础上提出了一种重调度算法,即LAUC_VF_RESCHEDULE算法,它的主要思想是：对新到达的突发运用LAUC_VF算法调度不成功时,将已经调度成功的突发从原有信道Ⅰ重新调度到另一数据信道J上,并保持该突发的到达时刻和结束时刻不变,从而将新到达的突发调度到数据信道Ⅰ上。仿真结果表明在大多数情况下该重调度算法相对于LAUC_VF算法对网络性能的改善是比较大的。     

设备故障条件下柔性作业车间重调度方法

设备故障是生产实践中最为常见的一类不确定事件,它易对正常的生产计划造成影响。为了有效应对生产中的设备随机故障干扰,对设备随机故障条件下的柔性作业车间调度问题进行了研究,提出了一种基于组合策略的重调度方法。在重调度方法中,对重调度成本进行了系统分析并建立了重调度成本函数,设计了两种重调度策略,并结合免疫算法对遗传算法进行了改进,用于模型的求解计算。通过算例分析,验证了方法的可行性和有效性。实验结果表明,所提出方法能够更好地处理多种情况下的设备故障扰动。     

Rescheduling Manufacturing Systems: A Framework of Strategies, Policies, and Methods

Many manufacturing facilities generate and update production schedules, which are plans that state when certain controllable activities (e.g., processing of jobs by resources) should take place. Production schedules help managers and supervisors coordinate activities to increase productivity and reduce operating costs. Because a manufacturing system is dynamic and unexpected events occur, rescheduling is necessary to update a production schedule when the state of the manufacturing system makes it infeasible. Rescheduling updates an existing production schedule in response to disruptions or other changes. Though many studies discuss rescheduling, there are no standard definitions or classification of the strategies, policies, and methods presented in the rescheduling literature. This paper presents definitions appropriate for most applications of rescheduling manufacturing systems and describes a framework for understanding rescheduling strategies, policies, and methods. This framework is based on a wide variety of experimental and practical approaches that have been described in the rescheduling literature. The paper also discusses studies that show how rescheduling affects the performance of a manufacturing system, and it concludes with a discussion of how understanding rescheduling can bring closer some aspects of scheduling theory and practice.     

New Grid Scheduling and Rescheduling Methods in the GrADS Project

The goal of the Grid Application Development Software (GrADS) Project is to provide programming tools and an execution environment to ease program development for the Grid. This paper presents recent extensions to the GrADS software framework: a new approach to scheduling workflow computations, applied to a 3-D image reconstruction application; a simple stop/migrate/restart approach to rescheduling Grid applications, applied to a QR factorization benchmark; and a process-swapping approach to rescheduling, applied to an N-body simulation. Experiments validating these methods were carried out on both the GrADS MacroGrid (a small but functional Grid) and the MicroGrid (a controlled emulation of the Grid).     

A Constraint-Based Robotic Soccer Team

It is a challenging task for a team of multiple fast-moving robots to cooperate with each other and to compete with another team in a dynamic, real-time environment. For a robot team to play soccer successfully, various technologies have to be incorporated including robotic architecture, multi-agent collaboration and real-time reasoning. A robot is an integrated system, with a controller embedded in its plant. A robotic system is the coupling of a robot to its environment. Robotic systems are, in general, hybrid dynamic systems, consisting of continuous, discrete and event-driven components. Constraint Nets (CN) provide a semantic model for modeling hybrid dynamic systems. Controllers are embedded constraint solvers that solve constraints in real-time. A controller for our robot soccer team, UBC Dynamo98, has been modeled in CN, and implemented in Java, using the Java Beans architecture. A coach program using an evolutionary algorithm has also been designed and implemented to adjust the weights of the constraints and other parameters in the controller. The results demonstrate that the formal CN approach is a practical tool for designing and implementing controllers for robots in multi-agent real-time environments. They also demonstrate the effectiveness of applying the evolutionary algorithm to the CN-modeled controllers.     

一种基于约束的多维数据异常点挖掘方法

数据中的异常点常常反映了企业经营中潜伏的问题或暗藏的商机,数据分析人员经常需要从大量的数据中找出这些异常点.最近提出的一种从数据中自动发现异常点的方法,将人们从繁重的体力劳动中解放出来.然而,该方法在计算效率和伸缩性方面还存在很多不足.针对这些不足,对该方法进行了优化和改进,提出了一种基于约束的多维数据异常点挖掘方法.通过在数据挖掘过程中引入约束条件,首先将数据立方体限制到一个小的多维空间,然后再从中找出异常点.实验结果表明该方法非常有效.     

基于约束的主动规则终止性分析

终止性是主动规则所需的最重要的一个性质,但规则的终止性检查通常是不可判定的.已有的静态分析方法非常保守,SQL3标准也没有提供保证终止的机制,所以商业数据库限制规则级联触发的最大次数确保终止.由于规则可看成数据库状态转换器,而约束能够表示所有可能的数据库状态,基于约束表示的数据库状态及约束求解,模拟规则处理,可得到更精确的终止性结论.     

The Localization and Correction of Errors in Models: A Constraint-Based Approach

Model-based diagnosis, and constraint-based reasoning are well known generic paradigms for which the most difficult task lies in the construction of the models used. We consider the problem of localizing and correcting the errors in a model. We present a method to debug a model. To help the debugging task, we propose to use the model-base diagnosis solver. This method has been used in a real application of the development a model of a railway signalling system.     

资源动态组织支持的网格依赖任务重调度机制

针对网格依赖任务重调度所面临的效率低与触发频繁的问题,提出资源动态组织支持的网格依赖任务调度机制.该机制以资源的动态组织为核心,基于资源动态性度量结果对资源进行性能聚类分析,并过滤性能相似资源中的强动态性资源,以在减少资源数量的同时提高重调度备选资源的稳定性.实验表明基于该机制的重调度算法保持了静态调度策略在动态网格环境下相对于动态调度策略的性能优势,从而验证了该机制解决网格依赖任务重调度所面临问题的有效性.     

Fuzzy Constraint-Based Agent Negotiation

Conflicts between two or more parties arise for various reasons and perspectives. Thus, resolution of conflicts frequently relies on some form of negotiation. This paper presents a general problem-solving framework for modeling multi-issue multilateral negotiation using fuzzy constraints. Agent negotiation is formulated as a distributed fuzzy constraint satisfaction problem (DPCSP). Fuzzy constrains are thus used to naturally represent each agent's desires involving imprecision and human conceptualization, particularly when lexical imprecision and subjective matters are concerned. On the other hand, based on fuzzy constraint-based problem-solving, our approach enables an agent not only to systematically relax fuzzy constraints to generate a proposal, but also to employ fuzzy similarity to select the alternative that is subject to its acceptability by the opponents. This task of problem-solving is to reach an agreement that benefits all agents with a high satisfaction degree of fuzzy constraints, and move towards the deal more quickly since their search focuses only on the feasible solution space. An application to multilateral negotiation of a travel planning is provided to demonstrate the usefulness and effectiveness of our framework.     

Excluding Symmetries in Constraint-Based Search

We introduce a new method, called symmetry excluding search (SES), for excluding symmetries in constraint based search. To our knowledge, it is the first declarative method that can be applied to arbitrary symmetries. The SES-method is based on the notion of symmetric constraints, which are used in our modification of a general constraint based search algorithm. The method does not influence the search strategy. Furthermore, it can be used with either the full set of symmetries, or a subset of all symmetries.We proof correctness, completeness and symmetry exclusion properties of our method. Then, we show how to apply the SES-method in the special case of geometric symmetries (rotations and reflections) and permutation symmetries. Furthermore, we give results from practical applications.     

SOG环境中工作流应用的服务重调度策略

在动态的SOG环境中,针对工作流应用执行中出现的服务故障问题,提出一个SRPS服务重调度策略。如果故障服务为服务图中关键路径上的节点,SRPS考虑采用基于效率的启发式方法对所有未执行的任务重新分配服务,否则SRPS采取基于稳定性考虑的单任务服务重调度。实验结果表明,SRPS策略在高动态性的SOG环境中优于SLACK方法及AHEFT方法。     

Constraint-Based Design of Embedded Intelligent Systems

Substantial progress has been achieved using the standard Constraint Satisfaction Problem framework. However, there is a major unsolved challenge confronting the constraint research community: the constraint-based design of embedded intelligent systems. This requires a new online model of constraint satisfaction and new computational tools for specifying, modeling, verifying and implementing constraint-based, hybrid, intelligent systems, such as robots. The Constraint Net model of Zhang and Mackworth allows the design of hybrid intelligent systems as situated robots: modeling the robot and the environment symmetrically as dynamic systems. If the robot's perceptual and control systems are designed as constraint-satisfying devices then the total robotic system, consisting of the robot symmetrically coupled to the environment, can be proven correct. Some theoretical and practical advances based on this model are described, including experiments with the constraint-based design of robot soccer players.     

基于约束的可定制产品配置模型

在分析可定制产品概念及其结构特点的基础上，通过采用可定制产品的形式化建模方法，实现了对可定制产品配置模型与可定制产品数据BOM的构建．利用可定制产品配置模型中的约束条件及相应的产品数据BOM的分解算法，并配合工程数据库技术，降低了企业产品数据管理的冗余和低效，实现了可定制产品数据在企业各部门间的集成、共享及一致性控制．     

面向航空发动机装配线的知识化制造系统重调度和自重构

为了解决航空发动机装配过程中存在的不确定返工问题,建立了面向航空发动机装配线的知识化制造系统(knowledgeable manufacturing system,KMS)重调度和班组自重构优化模型,提出装配线重调度及自重构集成优化算法.在算法调度层,证明了以加权完工成本为优化目标的工序排序性质,并对工序进行初始排序.定义了3种邻域结构,用变邻域搜索(variable neighborhood search,VNS)对工序在并行装配组上的指派问题和调度问题进行优化.在重构层,在不违背装配组装配技能约束的前提下利用装配线负载平衡原则对装配班组进行配置,并采用禁忌搜索(tabu search,TS)对班组配置进行优化.仿真实验结果表明了模型与算法的有效性.