考虑资源置信度的跨企业项目鲁棒性调度算法

资源不确定性高和调度鲁棒性要求高是跨企业项目调度问题的重要特征,本文采用资源置信度度量资源的不确定性,建立了考虑资源置信度约束的跨企业项目鲁棒性优化调度模型,设计了路径重连求解算法.算法以路径重连机制搜索解空间,以嵌入 的启发式时间缓冲插入算法快速生成鲁棒性调度,并可通过局部增强搜索算法进一步优化调度的鲁棒性.本文应用项目调度标准问题 库PSPLIB中大量问题实例进行了仿真实验,同两个当前具有代表性的鲁棒性项目调度算法进行了比较,实验结果表明了文中算法的有 效性与优势.     

IT项目进度计划风险量化预测方法

针对IT项目进度基线定义质量普遍偏低的问题,提出了一种资源约束条件下基于蒙特卡洛模拟的进度风险量化评估方法．首先,考虑资源对进度的限制问题,提出资源约束条件下的活动历时抽样方法;其次,提出在活动历时随机变化情况下,项目关键路径动态识别方法,研究项目工期概率分布问题．最后,通过实例表明,资源约束条件下的蒙特卡洛模拟方法,能够有效地评估IT项目中的进度风险,辅助项目决策．     

The development of a university sports complex: A project management application

The development of a university sports complex requires an integrated planning, scheduling and management approach, a requirement which is underscored by the desired to overlap design and construction activities in order to complete the facility on an accelerated schedule. The analysis of the project utilizes project management techniques: development of network models, identification of critical paths, and scheduling, cost control and resource allocation considerations. The use of computerized project planning and control tools provides flexibility and enables easy modification of the plans.     

(DP)SM: A dynamic approach to resouce constraint project scheduling

The purpose of this paper is twofold, first to introduce and evaluate a dynamic priority scheduling model developed in this research for solving the resource constraint project scheduling problem, second to introduce an improvement made upon the first model by cross breeding Dynamic Programming with the Dynamic Priority Scheduling Method (DPSM). The second model called Dynamic Priority Dynamic Programming Scheduling Method [(DP)²SM] aims at optimising the staged resource allocation decisions in DPSM. DPSM divides a project into phases (cycles) the length of which depend on the duration of the project and the period of clock cycle selected. The scheduling process starts by allocating resources to the first phase/cycle using a variety of policies, then the best schedule is selected based on an objective function. The process continues till all the activities are scheduled. In DPSM the interaction between phases is ignored while the decisions of each phase or cycle will affect all the remaining phases. Using (DP)² SM it may be possible to improve the quality of a schedule and reduce the duration of a project by optimising the overall project schedule.     

New concepts for activity float in resource-constrained project management

The concepts of float and critical path are central to analyzing activity networks in project management. In resource-constrained projects, schedule multiplicity makes it difficult to calculate float and identify critical activities accurately. In this work, new concepts of float and critical activity are developed to ascertain critical activities more precisely without reference to activity start and end times in specific schedules. The notions of float, group float, float set, negative float and zero critical activity are introduced, which the project manager can use to deal more effectively with critical activities, duration uncertainty, activity buffering, and resource allocation than the currently available tools in literature. For practical implementation, algorithms are provided and tested to calculate the new measures on the PSPLIB benchmark instances, specifically the J30, J60 and J120 test sets, for the resource constrained project management, illustrating the effectiveness of the proposed concepts in helping to identify flexibility in scheduling activities.     

Reactive scheduling in the multi-mode RCPSP

The multi-mode resource-constrained project scheduling problem (MRCPSP) involves the determination of a baseline schedule of the project activities, which can be executed in multiple modes, satisfying the precedence relations and resource constraints while minimizing the project duration. During the execution of the project, the baseline schedule may become infeasible due to activity duration and resource disruptions. We propose and evaluate a number of dedicated exact reactive scheduling procedures as well as a tabu search heuristic for repairing a disrupted schedule, under the assumption that no activity can be started before its baseline starting time. We report on promising computational results obtained on a set of benchmark problems.     

Project-driven planning and scheduling support for virtual manufacturing

The paper addresses the issue of decision-making support for small and medium-size enterprises operating within a virtual project-driven enterprise environment. The problem considered here can be defined in terms of finding a feasible schedule that satisfies the constraints imposed by the work-order duration, the price, and the time-constrained resource availability. The problem belongs to the class of multi-mode case problems of project scheduling, where finding a feasible solution is NP-hard. A heuristic method for process planning and scheduling is proposed. The method is based on a critical path approach and the branch and bound search scheme. It has been implemented in a web-enabled interactive software package, and is illustrated using the example of a virtual construction enterprise. Received: February 2005 / Accepted: January 2006     

Scheduling of linear projects with single loop structures

In the last decade, a number of linear scheduling methods based on the theories of linear and dynamic programming were developed for the scheduling of linear projects. However, these methods are only suitable for the scheduling of serial linear projects (i.e. sequential activities). In this paper, a nonserial dynamic programming formulation for the scheduling and control of linear projects that involve single loop structures is presented. The objective is to provide for the selection of crew formations, interruptions, and lags for the production activities that result in the minimum project duration. The advantage of this nonserial dynamic programming approach is its ability to handle both serial and nonserial linear projects with variable crew formations and work interruptions. In addition, the system presented produces a graphical representation of the project schedule of minimum duration and updates the original schedule based on current information supplied by the user. A numerical example is included to illustrate the input and output of the system presented.     

MRCPSP的一种精确算法

着眼于多模式资源受限项目调度方法,其特色在于,针对项目中每个任务的工期不仅取决于自身的执行模式,而且决于该工工时间的一般情形,同时考虑每个任务对可更新（再生）资源需求呈任意分布、可更新（再生）资源的最大供给量随时间而变化的一般情况,作为对前人研究成果的进一步推广,本文在经典单模式DH分枝定界算法的基础上,利用事件驱动的时间增量方式,成功地获得了这种最一般的项目调度问题的最优解。     

An integrated approach for requirement selection and scheduling in software release planning

It is essential for product software companies to decide which requirements should be included in the next release and to make an appropriate time plan of the development project. Compared to the extensive research done on requirement selection, very little research has been performed on time scheduling. In this paper, we introduce two integer linear programming models that integrate time scheduling into software release planning. Given the resource and precedence constraints, our first model provides a schedule for developing the requirements such that the project duration is minimized. Our second model combines requirement selection and scheduling, so that it not only maximizes revenues but also simultaneously calculates an on-time-delivery project schedule. Since requirement dependencies are essential for scheduling the development process, we present a more detailed analysis of these dependencies. Furthermore, we present two mechanisms that facilitate dynamic adaptation for over-estimation or under-estimation of revenues or processing time, one of which includes the Scrum methodology. Finally, several simulations based on real-life data are performed. The results of these simulations indicate that requirement dependency can significantly influence the requirement selection and the corresponding project plan. Moreover, the model for combined requirement selection and scheduling outperforms the sequential selection and scheduling approach in terms of efficiency and on-time delivery.     

基于活动工期风险和资源约束风险的缓冲大小计算方法

提出一种不确定情况下考虑活动工期风险和多资源约束风险的缓冲大小计算方法. 首先, 运用贝叶斯网络技术分析关键风险因素, 评估其造成的活动工期风险; 其次, 通过资源流网络方法衡量资源约束风险, 进而提出合理的缓冲配置方法以构建稳定的关键链调度计划. 通过算例分析和比较研究, 验证了所提出方法兼具有效性和实用性, 能够在保证较高按时完工率的同时, 有效缩短项目工期并保持进度计划稳定.

     

柔性工时约束下项目调度及其蚁群算法

针对软件工程项目调度问题,在考虑加班工时的情况下,提出了柔性工时约束下项目调度问题的数学模型,并设计了相应的蚁群算法。模型对项目人力资源的特殊性进行了分析,指出项目人力资源是一种特殊的可更新资源,在允许加班的情况下,人力资源构成特殊的柔性工时约束。针对所设计的数学模型,在并行项目进度生成机制基础上设计了蚁群算法,并通过算例进行验证与分析。     

The resource-constrained activity insertion problem with minimum and maximum time lags

This paper considers the resource-constrained activity insertion problem with minimum and maximum time lags. The problem involves inserting a single activity in a partial schedule while preserving its structure represented through resource flow networks and minimizing the makespan increase caused by the insertion. In the general case, we show that finding a feasible insertion that minimizes the project duration is NP-hard. When only minimum time lags are considered and when activity durations are strictly positive, we show that the problem is polynomially solvable, generalizing previously established results on activity insertion for the standard resource-constrained project scheduling problem.     

蚁群系统算法求解多模式资源约束项目调度问题

针对以工期最短为优化目标的多模式资源约束项目调度问题进行研究,在建立数学模型的基础上,通过设计合适的编码方式和调度生成策略,生成问题的构建图,定义新的信息素表示和启发式信息,提出一种改进的蚁群系统算法优化求解该问题。将模型和算法在工程项目调度实例中加以应用,验证了所提出的优化调度方法的正确性和有效性。     

基于关键链的资源受限项目调度新方法

针对资源受限项目调度问题（RCPSPs）的实际需求建立了多目标优化调度模型，综合运用现有研究成果，设计了基于关键链的项目调度方法。该方法首先采用基于优先规则的启发式算法生成工期最小的近优项目计划，再在该计划中嵌入输入缓冲和项目缓冲，保证项目计划在非确定环境下的稳定执行。论文引用RCPSPs的标准问题库PSPLIB中大量案例对算法进行了的仿真试验，结果表明本文方法较传统项目调度方法有很大改进，论文最后对仿真结果进行了深入讨论，并指出了未来的研究方向。     

基于广义资源日历约束的项目资源调配优化问题

资源受限项目调度问题(RCPSP)是最具代表性的项目调度问题之一,针对实际情况中考虑资源投入的必要性,建立一种以资源投入为变量的基于广义资源日历约束的项目调度优化模型.首先,引入组合优先关系的概念对广义资源日历的概念和具体内容进行整合和完善,为了避免传统网络图在表示组合优先关系时出现的网络循环等弊端,使用节点表示活动开始和结束的瞬时状态改进节点网络图;其次,考虑活动优先关系、活动持续时间、不可更新资源总量和资源日历约束,以项目工期最短和项目成本最小为优化目标,运用CP优化器求解所建立的多目标优化模型;最后,通过设计仿真算例并进行数值实验验证模型的准确性和高效性.     

基于动态关键路径的仿真网格资源调度算法

从仿真系统工作流的关键路径分析，确定关键路径上的联邦成员节点，使网格资源调度方面优先获得保证。簦于仿真网格系统运行的复杂性和不确定性，引入了随机规划理论，提出了仿真网格的动态关键路径概念以及基于动态关键路径的资源调度算法，共同解决当资源有限以及任务相关情况下仿真网格的资源调度问题。具体实现，主要使用遗传算法以及MCP算法。仿真实验结果表明，基于动态关键路径的资源调度算法能够优化仿真网格资源的调度。     

Project-oriented task scheduling for mobile robot team

This paper presents a project-oriented framework for multi-robot task scheduling. An agent-based architecture is designed to schedule tasks where robots are considered as resources. The study focused on the problems when the number of available robots is less than the required number. In this case, the problem becomes a resource-constrained scheduling problem. Initially, tasks are scheduled by using Critical path method (CPM), resource leveling method is used to smooth the deviation between the resource requirements and available resource levels, and tasks are allocated to robots. As robots perform their tasks, a monitoring agent observes them and tasks are rescheduled if the difference between the planned and actual completion time of tasks exceeds a predefined threshold. Effectiveness of the proposed approach is shown by using a nine-task two-robot project simulation.     

资源受限多项目调度问题的两阶段算法

在资源受限项目调度问题中,将可更新资源进一步拓展为具有胜任力差异的人力资源,建立考虑胜任力差异的人力资源受限多目标项目调度问题模型.该模型是对传统多模式资源约束项目调度问题更接近研发项目群实际的扩展.针对模型提出两阶段优化算法,第1阶段是项目时序约束优化阶段,采用蚁群算法(ACO)进行任务列表的优化求解,通过对信息素增量规则的改进、串联进度生成机制(SSGS)及资源冲突消解策略的使用,使蚁群算法的求解效率和质量得以提高;第2阶段是资源约束优化阶段,以第1阶段求得的优化任务列表为输入,逐项对人力资源约束进行核查与调整,最终生成项目调度的优化方案.数值实验表明,考虑胜任力差异的数学优化模型更符合研发项目群管理实践,同时两阶段算法在求解质量方面具有良好性能.     

A study of combining heuristics for scheduling projects with limited multiple resources

The main objective of this study was to find a simple and quick procedure on the microcomputer for scheduling activities of a constrained multiple resource single project network that would minimize project duration. From this research there are two different types of results presented. First, a combination of simple heuristics which find the average of the minimum project durations for the constrained resource problem is presented. This combination not only supports the previous research on successful simple heuristic methods which set the priorities for constrained resource problems, but also produces results which are significantly better than those obtained by single heuristics. Second, a procedure for determining this combination of heuristics is introduced. A computer algorithm, COMAL, was developed for this study with constrained resource problems, but in the future its use may be expanded into other fields.