基于随机活动工期的现金流动态均衡前摄性与反应性项目调度优化

承包商的现金流动态均衡对不确定条件下项目的顺利实施有重要影响。作者研究基于随机活动工期的现金流动态均衡前摄性及反应性项目调度问题,目标是在随机活动工期条件下,为承包商生成现金流均衡基准进度,并根据执行过程中的实际情况,动态地对其进行反应性调整。首先,通过建立前摄性调度优化模型生成基准进度,并提出两个反应性调度策略对其进行调整。其次,为以上诸模型的求解设计了模拟退火和禁忌搜索相结合的混合算法tabu-SA。最后,针对前摄性调度模型,在随机生成的算例集合上对算法进行测试,并进行大规模仿真实验。研究结果可以为随机活动工期下承包商保持现金流动态均衡、确保项目顺利实施,提供定量化决策支持。     

随机活动工期下考虑缓冲成本及效用的融资费用最小化项目调度优化研究

巨额融资所带来的高昂融资费用，推高承包商的总成本，严重挤压其利润空间。承包商迫切需要对项目现金流进行优化，提高资金配置效率，降低融资费用。此外，为了应对不确定性干扰，承包商通常花费事前成本为活动添加时间缓冲，以保证进度计划稳定性，以减少事后变更和调整费用。因此，本文研究随机活动工期下考虑缓冲成本及效用的融资费用最小化项目调度优化研究，旨在为承包商生成具有一定鲁棒性的融资费用最小化基准进度。首先，界定研究问题并构建优化模型，在此考虑为活动插入时间缓冲所带来的成本及效用。其次，设计VNTS混合算法对模型进行求解，提炼相关性质以提高算法搜索效率，并在算例集合上进行算法测试。最后，通过案例对本文研究进行说明。研究结果可以为随机活动工期下承包商控制融资费用、提高项目收益，提供定量化决策支持。     

多种费用下具有时间转换约束的工期费用均衡项目调度研究

传统离散时间-费用均衡项目调度问题DTCTP未考虑各个活动执行时间差别,本文将时间转换约束引入传统DTCTP,同时考虑项目间接费用和联系合同双方的奖惩费用,形成多种费用条件下具有活动类型时间转换约束的工期-费用均衡项目调度模型DTCTPTSC,并对模型进行优化分析.实例结果表明,间接费用率对工期-费用决策产生影响的阈值减小,业主设置的奖惩因子对承包商的激励约束效果具有区间响应特点;进一步从业主和承包商双方角度探讨了奖惩因子的取值对各自行为的影响,分析结果对双方在项目谈判过程中具有借鉴意义.     

基于里程碑支付的多模式多项目现金流平衡调度优化

现金流入与流出的动态平衡，对于承包商平稳实施项目具有重要的现实意义。本文基于这一实际背景，研究了在里程碑支付条件下，活动具有多种执行模式的多项目现金流平衡调度问题。首先，在对研究问题进行界定的基础上，构建了多模式多项目现金流平衡调度优化模型并提炼了模型的基本性质；其次，针对问题的NP-hard属性，开发了禁忌搜索启发式求解算法，根据问题性质提出算法的改进措施；最后，用一个实际案例对模型和算法进行了验证，得到如下管理启示：基于最大现金流缺口发生时段，适当延后相关里程碑活动的完成时间或调整相关非里程碑活动的开始时间，同时，根据现金流分布合理平移部分单项目的进度计划，能实现现金流出与流入的最佳匹配并有效减小最大现金流缺口。     

银行授信约束多模式工期最小化项目进度问题研究

本文研究银行授信额度约束下活动具有多种执行模式的工期最小化项目进度问题。首先对所研究问题进行界定;随后采用基于事件的研究方法构建了问题的整数规划优化模型;鉴于问题的NP-hard属性,设计了双层模拟退火搜索嵌套的启发式求解算法;最后对一个算例进行了求解分析,讨论了银行授信额度对项目进度安排及完成时间的影响。结果表明:随着银行授信额度的提高,承包商安排项目进度的可用资金随之增加,使得项目可以在较短的时间内完成;然而,如果在此过程中业主对承包商的支付总量保持不变,那么承包商的项目收益会随完成时间的提前而下降。     

柔性工期下的资源受限项目调度双目标优化研究

在项目调度过程中,活动工期应根据项目截止工期以及资源供给情况进行合理设置,而在传统的资源受限项目调度问题(RCPSP)中,活动的工期往往是已知且固定的,这在一定程度上限制了项目调度的灵活性。多模式下的项目调度方式虽然弥补了这一缺点,但其提供的工期-资源组合种类固定且有限,并不一定能保证包含最优的工期-资源组合。本文将活动工期作为项目调度问题的决策变量,允许其在一定范围内取值。这种柔性工期调度方式虽然增加了项目调度难度,但提高了项目调度灵活性,同时可以起到压缩项目完工时间的作用。为验证柔性工期调度方式对项目工期和成本的影响,本文建立了工期-成本双目标权衡优化模型,设计了两阶段嵌套算法(NSGAⅡ-RS)对其求解,实验证明,柔性工期调度策略是一种鲁棒性较好的项目完工时间压缩策略。     

活动执行时间可提前的多模式反应性项目调度优化

研究不确定活动工期下活动执行时间可提前的多模式反应性项目调度问题。首先对反应性研究现状进行综述;其次建立以最小化反应性总成本为目标的优化模型;随后基于问题特点设计禁忌搜索算法;最后通过具体案例分析关键参数对反应性成本的影响,并得出结论:执行时间提前得到的反应性成本及完工时间明显低于执行时间不可提前的结果;随着项目推进,总成本及影响的活动数量总体上呈减小趋势,但项目完工时间在某些时刻维持不变;对于工期增加较大的活动,将其本身或紧前活动提前启动,或将其转换至活动工期较短的模式可降低反应性成本。研究可为不确定环境下反应性计划制定提供决策支持。     

基于MAS的多模式分布式资源约束多项目调度

针对实践中分布式多项目的活动往往具有多种执行模式,提出多模式分布式资源约束多项目调度问题。在项目动态到达环境下,考虑活动不同的执行模式,以工期最短和多项目延期成本最小为目标分别构建局部单项目调度模型和全局多项目决策模型,采用改进变邻域搜索算法求解初始局部调度计划,并设计基于模式调整的全局协商调度算法求解全局决策模型,通过双层算法实现分布式多项目调度中局部单项目调度与全局多项目调度系统性协调,减少项目中断和多项目延期成本。基于构建的多模式测试集进行的多项目数值实验表明：本文设计的双层算法可有效求解多模式分布式多项目调度问题,并且对不同规模问题求解具有良好的适应性。     

一种求解柔性资源约束前摄性项目调度问题的启发式算法

在不确定环境中,一个具有较高鲁棒性的进度计划可以保证项目的稳定实施。考虑到现实中资源可能具有多种技能,会对制定鲁棒性较高进度计划的过程产生影响,因此本文研究了柔性资源约束下前摄性项目调度优化问题。首先界定研究问题;然后从鲁棒性最大化的视角出发,构建了研究问题的优化模型,在对模型进行分析的基础上将其分解为经典鲁棒优化和资源技能分配两个子模型;随后设计了求解问题的基于削峰算法的启发式算法;最后用一个实际案例验证了算法有效性,并分析了关键参数对进度计划鲁棒性的影响,得到如下结论:项目进度计划鲁棒性随着项目工期的延长、资源可用量的增加或资源柔性的提高而增大。     

双渠道下制造商现金流套期保值决策研究

由于汇率、利率、商品价格的变化以及双渠道供应链关系的复杂性,企业的现金流存在较大的波动性。本文研究双渠道销售模式下,制造商对现金流进行套期保值的决策问题。重点关注垄断企业在拥有一个分销商和线上销售的双渠道销售模式下,并利用内部融资将现金流用于提高生产效率时,如何根据现金流的波动程度、市场需求、替代产品敏感系数以及批发价格进行套期保值决策。研究了双渠道销售模式下制造商的均衡问题,比较了两种决策下的均衡解,并通过数值分析给出了直观的结论:市场最大需求与替代产品敏感系数增加时,企业更倾向于选择套期保值;现金流波动程度与批发价格增加时,企业更倾向于不选择套期保值。     

具有质量差异的项目支付进度问题研究——以软件项目为例

目前带有惩罚结构的项目支付进度模型通常以时间或成本为激励因子,来约束承包商保证进度和节约成本,未考虑质量因素对支付进度的影响。质量是项目管理的主要目标和决定项目成败的关键因素,研究质量对项目支付进度的影响有助于激励承包商提高表现从而保证项目质量。以软件项目为例,以软件产品质量为激励因子, 分别从承包商和客户的角度构建现金流净现值最大化为目标的项目支付进度优化模型,分析承包商表现水平及风险规避对双方收益的影响。针对模型的特点设计了遗传算法和禁忌搜索算法的混合算法求解模型。最后通过算例分析表明, 质量激励因子对项目的支付进度和双方的收益均存在较大的影响,为双方协商支付进度提供决策支持。     

On modelling payments in projects

Projects are often evaluated on financial performance. The net present value (NPV) has long been established as a highly relevant criterion in the management and control of projects. Research in this area has emphasised scheduling of activities in projects to maximise the contractor's NPV assuming that cash flows (both positive and negative) that occur over the duration of the project are known. In practice, however, the contractor usually knows the expenses associated with project activities. He can use this information combined with the knowledge of other project parameters such as activity durations to negotiate the payments received for completed work so that the project achieves the maximum level of financial returns. Extending previous research, this paper examines the problem of simultaneously determining the amount, location and timing of progress payments. We present several models and their solutions for an example problem. Based on the assumptions made, the models are applicable in different project environments. The problem and models presented here can be used by the contractor and client for managing cash flows, setting milestones, and negotiating critical contract parameters, in addition to identifying the location, timing, and amount of progress payments. They also contribute to the body of research on formulating and solving difficult combinatorial optimisation problems.     

基于融资能力约束的多模式Max-npv项目调度优化: 双重视角

从项目双方的视角出发,研究融资能力约束下的Max-npv项目调度问题。首先进行问题界定,构建由两个子模型构成的多模式Max-npv项目调度优化模型。随后,鉴于问题的强NP-hard属性,设计针对两个子模型迭代循环求解的禁忌搜索启发式算法,得到项目双方都满意的解。最后用一个实际案例对研究进行验证说明,并分析关键参数对合同双方收益的影响,结果表明:与实际进度安排相比,满意进度安排下合同双方的收益均有显著的提升;承包商和业主的融资能力、项目截止日期、承包商收益底线、折现率及支付比例均会对双方的收益产生重要影响。     

独立项目的久期预估与融资优化研究

项目投资与融资匹配程度,不仅关系到项目资金成本的大小,还体现对项目利率风险的对冲。基于债券久期的概念内涵,提出了项目久期与融资结构久期的概念及计算方法。以具体项目的投融资为案例进行研究,对案例公司已拟定的针对独立项目的债券融资方案进行投融资久期匹配、各期现金流匹配评价,并从市场利率曲线中发现融资成本优化空间,从投融资久期差及各期投融资现金流量差中找到优化融资的方案。以此提出结论:项目久期与融资结构久期的匹配是降低项目利率风险的重要手段;应综合融资结构久期与项目久期、现金流大小选择融资结构。     

Project Scheduling under Time Dependent Costs – A Branch and Bound Algorithm

In a given project network, execution of each activity in normal duration requires utilization of certain resources. If faster execution of an activity is desired then additional resources at extra cost would be required. Given a project network, the cost structure for each activity and a planning horizon, the project compression problem is concerned with the determination of optimal schedule (duration) of performing each activity while satisfying given restrictions and minimizing the total cost of project execution. This paper considers the project compression problem with time dependent cost structure for each activity. The planning horizon is divided into several regular time intervals over which the cost structure of an activity may vary. But the cost structure of the activities remains the same (constant) within a time interval. Key events of the project attract penalty for finishing earlier or later than the corresponding target times. The objective is to find an optimal project schedule minimizing the total project cost. We present a mathematical model for this problem, develop some heuristics and an exact branch and bound algorithm. Using simulated problems we provide an insight into the computational performances of heuristics and the branch and bound algorithm.     

Discrete-continuous project scheduling with discounted cash inflows and various payment models—a review of recent results

In this work discrete-continuous project scheduling problems with discounted cash flows are considered. These problems are characterized by the fact that activities of a project simultaneously require discrete and continuous resources for their execution. A class of these problems is considered, where the number of discrete resources is arbitrary, and there is one continuous, renewable resource, whose total amount available at a time is limited. Activities are non-preemptable, and the processing rate of an activity is a continuous, increasing function of the amount of the continuous resource allotted to the activity at a time. A positive cash flow (cash inflow) is associated with each activity, and the objective is to maximize the net present value (NPV). The discrete-continuous resource-constrained project scheduling problem with discounted cash flows (DCRCPSPDCF) is defined. Four payment models are considered: lump-sum payment at the completion of the project, payments at activity completion times, payments at equal time intervals, and progress payments. Some properties of optimal schedules are proved for two important classes of processing rate functions: all functions not greater than a linear function (including linear and convex functions), and concave processing rate functions.     

基于不同奖惩机制项目支付进度优化:双重视角

奖惩机制会对合同双方的收益产生重大影响,本文基于承包商和业主的双重视角,对不同奖惩机制下项目支付进度优化问题进行了研究。首先对所研究问题进行界定,并分别基于承包商和业主视角构建了不同奖惩机制下的优化模型;基于模型的属性设计了模拟退火启发式算法;最后通过一个实例对比了承包商和业主在四种不同奖惩机制下收益的优化结果,并对其中的关键参数进行了敏感性分析。结果显示:不同的奖惩机制对承包商和业主的收益有较大影响;不同的奖惩强度也会影响承包商和业主的收益。通过对奖惩机制类型及强度的分析,可以为项目中奖惩机制的设置提供定量化决策支持。     

A Two Stage Search Heuristic for Scheduling Payments in Projects

When the Net Present Value (NPV) of a project is used as a measure of its financial performance, effective management of cash flows over the duration of the project is critical for improved profitability. Progress payments are a major component of project cash flows. In many project environments, the contractor can negotiate payment terms. Payments are typically tied to completion of project activities and therefore have significant impact on the schedule of activities and the timing of the payments. In this paper, we consider the problem of simultaneously determining the amount, timing and location of progress payments in projects to maximize NPV. Due to the combinatorial nature of the problem, heuristics are a practical approach to solving the problem. We propose a two-stage heuristic where simulated annealing is used in the first stage to determine a set of payments. In the second stage, activities are rescheduled to improve project NPV. We compare the performance of this general purpose heuristic with other problem-dependent heuristics from the literature. Our results indicate that the simulated annealing heuristic significantly outperforms the parameter-based heuristics. Although rescheduling in the second stage improves NPV, increases are relatively small in magnitude. While the specific parameters settings suggested by the simulated annealing heuristic in this study may have limited generalizability at this time due to the narrow range of problems tested, our analysis suggests that a pure simulated annealing approach is a very attractive alternative for obtaining good heuristic solutions to the complex problem of scheduling payments in projects.     

Simulated annealing and tabu search for multi-mode resource-constrained project scheduling with positive discounted cash flows and different payment models

In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. A project is represented by an activity-on-node (AoN) network. A positive cash flow is associated with each activity. Four different payment models are considered: lump-sum payment at the completion of the project, payments at activities' completion times, payments at equal time intervals and progress payments. The objective is to maximize the net present value of all cash flows of the project. Local search metaheuristics: simulated annealing and tabu search are proposed to solve this strongly NP-hard problem. A comprehensive computational experiment is described, performed on a set of instances based on standard test problems constructed by the ProGen project generator, where, additionally, the activities' cash flows are generated randomly with the uniform distribution. The metaheuristics are computationally compared, the results are analyzed and discussed and some conclusions are given.