在单资源约束项目中的关键链管理

Dr.Goldratt于1986年提出了Theory of Constraint(TOC),强调以系统的观点来进行项目管理。TOC在项目中的运用被称为关键链管理(CCPM),它着眼于项目的关键链,并利用缓冲器来控制项目进程。本文在单资源约束下,以TOC为核心思想,提出了一个进行关键链管理的方法,从而改进了TOC在项目管理中的可操作性。     

基于PERT/CPM的关键链管理

网络规划技术是现代项目管理技术的重要组成部分。本文在对传统PERT/CPM网络规划方法分析的基础上,针对PERT三点估计在应用上的缺陷,引入Theory of Constraint(TOC),并对PERT三点估计给出一种全新的解释。在新的解释下,TOC思想在项目规划中的运用被称为关键链管理(CCPM),强调在项目实施过程中加强对关键链的管理。为此,本文提出了一个基于三点估计的关键链管理的新方法,并通过实例论证关键链管理作为一种新的项目管理方法可以接近或者超过PERT/CPM的平均效果。     

多资源约束下基于关键链的项目群工期-费用优化

现有工期压缩模型未考虑资源约束下多合同项目工期压缩所产生的局部效应与整体效应,针对这一局限性,通过引入子网络,分析了基于关键链法的项目群工期—费用优化机理,据此,对项目群初始网络计划进行工期优化。借助关键链,除去计划工期的冗余时间,动态调整存在资源冲突的合同项目开始时间。在此基础上,分析工期动态优化对关键链和非关键链合同项目压缩费用产生的不同影响以及对子网络自身和项目群的影响。基于此,研究并构建了多资源受限下单一子网络和项目群工期-费用优化模型。最后,结合算例,分析了优化模型的可行性和优势。研究结果表明：模型能够有效地解决资源约束下项目群计划调整和工期-费用优化问题,从而能够为业主科学安排项目群中各合同项目的起始时间和资源计划提供依据。     

关键链在项目进度管理中的应用

本文首先对关键链管理的基本方法和其隐含假设进行了分析,然后介绍了关键链管理方法在项目进度管理中的实施步骤。     

考虑资源可替代性的关键链调度方法研究

作为约束理论在项目管理领域的直接应用而产生的新方法,关键链技术在其诞生之初便引起了广泛关注.在简要介绍关键链基本理论的基础上,提出在识别关键链的过程中应考虑资源可替代性的影响.然后,以工期最小为目标与工期-成本权衡目标建立关键链识别方法模型,并通过算例验证了该方法的有效性.     

关键链多项目调度中分散式能力约束缓冲设置法

能力约束缓冲的设置问题是关键链多项目管理法的核心问题,对成功执行关键链多项目调度非常重要.本文考虑了使用“鼓资源活动之间存在间隙的特点,分析了集中设置能力约束缓冲方法的不足之处,提出了分散式能力约束缓冲设置法.该法阐述了能力约束缓冲在“鼓”计划中的配置位置和大小.然后通过数据实验将该法与集中式能力约束缓冲设置法进行了比较,结果表明:集中式能力约束缓冲会产生过大或者过小的缓冲,而分散式能力约束缓冲设置法能针对不同的“鼓”计划设置合适的缓冲大小.特别当“鼓”活动间隙靠近最后一个“鼓”活动时,分散式设置法能提供更短的项目群计划完工期,同时得到与集中式设置法一样的按时完工率,以及较低的缓冲超出概率.     

资源约束下多项目调度的改进遗传算法

针对资源约束下的多项目调度问题,在前人提出的有效的启发式算法研究路径基础上,本文利用遗传算法,结合进度生成机制,提出了多项目调度的改进遗传算法。与其他多项目调度启发式算法相比,该算法在平均项目延迟和最佳解比例方面都表现较好,综合利用优化后的优先规则也使得该算法更适用于不同网络复杂度和不同资源约束程度的多项目调度问题中。     

消除二次资源冲突的鲁棒性双目标关键链项目调度优化

传统关键链方法无法解决插入输入缓冲引起的二次资源冲突困境,更不能表述和建模调度方案的鲁棒性,这极大地限制了它在项目进度管理中的广泛应用。本文从鲁棒调度和双目标优化两个角度拓展和创新了传统关键链方法。首先,针对最棘手的二次资源冲突困境,从鲁棒优化视角提出基于局部重调度的二次资源冲突消除策略,进而设计基于消除策略的鲁棒性测度指标;其次,构建同时优化项目工期和调度方案鲁棒性的双目标关键链项目调度模型,并设计混合差分进化算法求解。在获取基准调度计划阶段为克服现有的关键链识别方法的不足,设计基于鲁棒性资源流网络的关键链识别算法并将其嵌入差分进化主算法中。最后,设计并运行大规模数值测试实验,输出数据的统计结果验证了关键链识别算法和二次资源冲突消除策略的有效性,同时也表明了本文设计混合差分进化算法的优越性。     

A Model for Resource Constrained Production and Inventory Management

We present a general model for multi-item production and inventory management problems that include a resource restriction. The decision variables in the model can take on a variety of interpretations, but will typically represent cycle times, production batch sizes, number of production runs, or order quantities for each item. We consider environments where item demand rates are approximately constant and performing an activity such as producing a batch of a product or placing an order results in the consumption of a scarceresource that is shared among the items. Some examples of shared resources include limited machine capacity, a restriction on the amount of money that can be tied up in stock, orlimited storage capacity. We focus on the case where the decision variables must be integer valued or selected from a discrete set of choices, such as when an integer number of production runs is desired for each item, or in order quantity problems where the items come in pack sizes containing more than one unit and, therefore, the order quantities must be an integer multiple of the pack sizes. We develop a heuristic and a branch and bound algorithm for solving the problem. The branch and bound algorithm includes reoptimization procedures and the heuristic to improve its performance. Computational testing indicates that the algorithms are effective for solving the general model.     

Robust Resource Allocation Decisions in Resource‐Constrained Projects*

The well‐known deterministic resource‐constrained project scheduling problem involves the determination of a predictive schedule (baseline schedule or pre‐schedule) of the project activities that satisfies the finish–start precedence relations and the renewable resource constraints under the objective of minimizing the project duration. This baseline schedule serves as a baseline for the execution of the project. During execution, however, the project can be subject to several types of disruptions that may disturb the baseline schedule. Management must then rely on a reactive scheduling procedure for revising or reoptimizing the baseline schedule. The objective of our research is to develop procedures for allocating resources to the activities of a given baseline schedule in order to maximize its stability in the presence of activity duration variability. We propose three integer programming–based heuristics and one constructive procedure for resource allocation. We derive lower bounds for schedule stability and report on computational results obtained on a set of benchmark problems.     

The Impact of Learning and Labor Attrition on Worker Flexibility in Dual Resource Constrained Job Shops

This study investigates the impact of worker learning, worker flexibility, and labor attrition on the system performance of a dual resource constrained (DRC) job-shop. The effects of learning and labor attrition have not been previously addressed in DRC literature. Results from the study, consistent with previous literature, show that the greatest benefits are achieved when inter-departmental worker flexibility is incrementally introduced into the system. In addition, the learning environment, which depends on the initial processing time of jobs and the learning rates of workers, is shown to impact the acquisition of flexibility. The study also shows that the impact of labor attrition on system performance under certain shop conditions may be significant.     

西部地区煤炭资源开采与环境的耦合效应研究

煤炭是我国的主要能源,煤炭生产利用过程中产生的环境问题是我国环境问题的主要成因。我国东部地区煤炭资源开采活动经历了投产→成熟→衰退的过程,对环境问题多属于末端管理,由此产生了巨大的环境损失与环境管理成本。而这种资源开采模式对生态环境脆弱的西部地区是行不通的,因此,应在西部地区资源开采的初始阶段,即在资源开采未对环境产生重大影响之前做好环境管理工作,这是西部地区煤炭资源开采活动需要重点解决的问题。     

Liquidity Constrained Markets Versus Debt Constrained Markets

This paper compares two different models in a common environment. The first model has liquidity constraints in that consumers save a single asset that they cannot sell short. The second model has debt constraints in that consumers cannot borrow so much that they would want to default, but is otherwise a standard complete markets model. Both models share the features that individuals are unable to completely insure against idiosyncratic shocks and that interest rates are lower than subjective discount rates. In a stochastic environment, the two models have quite different dynamic properties, with the debt constrained model exhibiting simple stochastic steady states, while the liquidity constrained model has greater persistence of shocks.     

外部环境、内部资源与企业社会责任

外部环境和内部资源如何影响企业履行社会责任?本文以中国制造业上市公司2011-2013年数据为样本,研究制度环境(舆论压力)和市场环境(竞争强度)对企业履行社会责任的影响,以及企业内部两种类型资源的调节作用。研究表明,舆论压力会促进企业履行社会责任,而竞争强度与企业履行社会责任呈"∩"形关系。进一步研究发现,企业资源(政治关系和冗余资源)正向调节外部环境对企业履行社会责任的影响。     

人才环境及基于神经网络的陕西经济发展预测模型研究

利用多层前馈神经网络的反传算法(BP算法),在建立陕西人才环境评价指标体系的基础上,采用MATLAB软件建立了人才环境与经济发展关系的神经网络模型,映射出各年人才环境指标与人均GDP指标之间的函数关系,此BP神经网络可以成功地根据陕西人才环境指标对经济发展进行预测。     

电子商务环境下的DSS应用模式及资源描述

分析了传统DSS的弊端,引出电子商务环境下的DSS应用新模式。针对原有决策电子市场的框架结构,进行相对的完善,给出了一个新决策电子市场模型,并分析了新模式下完成一次交易事务的全过程。在此基础上,阐述了决策资源描述的重要性,并根据owl-s描述Web服务的框架,对电子市场中的DSS资源进行针对性的描述。利用新市场模型和资源描述框架,可以有效完善市场功能并形成新模式下相对通用的DSS资源描述方案。     

Unemployment in a Bankruptcy Constrained Model

This paper proposes a model of labour demand based on a bankruptcy constrained firm. This implies two different regimes for the process generating labour demand: one when this bankruptcy constraint is not binding and one when it is. The same applies to unemployment. This unemployment model is applied to U.S. quarterly data, where account is being taken of the two regimes by dummy variables based on the turning points of the NBER business indicator. It appears that the variables affecting U.S. unemployment in the respective regimes are also the ones predicted by our theoretical model.