基于蒙特卡罗法的施工成本扰动风险研究

针对项目施工过程中成本风险对企业影响最为深远这一问题,利用蒙特卡罗方法对工程项目施工阶段成本的风险特性进行有效分析。而依据成本分析的蒙特卡罗方法建立的工程项目成本风险指标体系的模型,能够对成本进行估算能够达到预期效果,不仅有助于提高投资决策的可靠性,而且有助于了解项目所承受的各种风险,便于提出各种措施提高应对项目成本风险的能力。     

Uncertainty Processing and Risk Monitoring in Construction Projects Using Hierarchical Probabilistic Relational Models

Construction projects do not often reach their expected results regarding time, cost, and quality, due to the internal and external environment variations. Despite a substantial literature about risk management, no generic approach is proposed to represent construction project considering together technical and human dimensions or sustainability with their uncertainties. Modeling complex dynamical systems from heterogeneous pieces of knowledge varying in precision and reliability is a challenging task. This article proposes an innovative generic and versatile approach, based on the formalism of hierarchical probabilistic relational models to analyze and to propagate uncertainty in construction project regarding different levels of knowledge. The aim is to obtain a flexible, portable, and versatile model able to simulate the behavior of complex system's entities involved in any construction project at different levels of detail while taking uncertainty into account. To illustrate and highlight this approach, an academic example and a real case are proposed.     

Knoledge-Based Systems and Fuzzy Sets in Risk Management

An integrated microcomputer-based knowledge system is developed for risk management in construction. The system (Expert-Risk) applies the concepts of fuzzy set theory to evaluate the overall risk of a project. It is also integrated with various rerlational data bases that provide the system with financial and cost data necessary for bankruptcy and risk analysis. Today's construction industry involves more dynamic and construction industry involves more dynamic and uncertain planning than ever before. without professional risk management, decision makers cannot systematically approach complex problemx. The system provides a more definitive perception of the overall risk of a construction project, and a more rational basis for contingency planning and evaluation. The system allows management to focus on those risk factors which have significant impact on planning.     

应对不确定性的水利工程项目责任成本测算方法

成本控制对提高项目管理水平、扩大项目利润空间具有重要意义。责任成本测算作为工程项目成本控制的有效方法被许多企业认可,但是工程项目的许多不确定性限制了这种方法的应用。以水利工程项目群为基础,从概率论的角度分析了人为、环境等不确定性因素对责任成本测算的影响,并提出应对不确定性的具体措施。针对水利工程项目特点对责任成本测算方法进行研究,提出了“小循环”成本测算方法,将不确定性因素产生的总影响考虑在责任成本测算额之内,为项目成本测算的合理性与准确性提供了思路,并为责任成本测算在水利工程项目中的应用提供了方法。     

Using the MD CAD model to develop the time–cost integrated schedule for construction projects

Time and cost are two critical factors determining the success of a construction project. However, it is still a daunting task for project planners to develop a time–cost integrated schedule due to the tremendous amount of information that need to be processed. Various research efforts have been made to develop model-based systems to facilitate information processing and integrate time and cost throughout the project life cycle. However, the results of the previous studies are not comprehensive enough to fulfill the requirements of project management. This paper presents a scheduling system that applies Multi-Dimensional (MD) CAD model, Object Sequencing Matrix (OSM), and genetic algorithms (GAs) to generate the time–cost integrated schedule for the construction project. A computer implementation called MD CAD model-based Project Scheduling System (MD_PSS) is also developed to verify the feasibility of the proposed approach.     

Cost simulation in an item-based project involving construction engineering and management

Despite the extensive use of simulation in management, the continuous simulation model for cost estimation remains unexploited, especially for construction engineering and management. This study introduces streamlining Monte Carlo simulation procedures with evaluation of stochastic processes and input probability distribution selection via hypothesis testing, and specification of correlations between simulated variates. By using self-developed algorithms and a spreadsheet-add-on program, this investigation uses historical construction projects as case study data to create an early-stage cost distribution for budget allocation. While establishing the applicability of the proposed simulation procedures, this study demonstrates that the simulated cost results present superior simulation accuracy in addition to separating the principal work items and unit price component model. Generally, the precision and absolute error rates fall into acceptable ranges when the proposed systematic simulation procedures are adopted. The cost simulation approach offers a simplified decision tool for fairly assessing construction cost and uncertainties based on the experienced judgment of project managers.     

Stochastic time-cost optimization using non-dominated archiving ant colony approach

This article employs a non-dominated archiving ant colony approach to solve the stochastic time-cost trade-off optimization problem. The model searches for non-dominated solutions considering total duration and total cost of the project as two objectives. In order to expect more realistic outcomes for the time-cost trade-off problem, uncertainties in time and cost of the project should be taken into account. Fuzzy sets theory is used to answer for uncertainties in time and cost of the project. The model embeds the α-cut approach to account for accepted risk level of the project manager. Left and right dominance ranking method is used for finding non-dominated solutions. The ranking method employs decision maker's optimism using β concept. The performance of the model is tested according to performance metrics for multi-objective evolutionary algorithms proposed in the literature. The results show that the algorithm is adequately reliable. A case study is solved to show the application of the proposed model for the uncertain time-cost trade-off problem.     

Fuzzy-based MOGA approach to stochastic time–cost trade-off problem

In construction projects, time and cost are manageable objectives with significant interdependencies for which sets of trade-offs may exist. This study presents a new approach for the solution of time–cost trade off problems in an uncertain environment. Fuzzy numbers are used to address the uncertainties in the activities execution times and costs. Fuzzy sets theory is then explicitly embedded into the optimization procedure. A multi-objective genetic algorithm is specially tailored to solve the discontinuous and multi-objective fuzzy time- cost model with relatively large search space. The proposed approach identifies the best set of implementation options defined by the sets of non-dominated solutions Accepted risk level and optimism of the decision maker are addressed using α-cut approach and optimism index (β) respectively. To illustrate the application and performance of the model, two case examples are presented, for which separate Pareto fronts are developed. The fuzzy presentation of the non-dominated solution helps the project manager to apply his own level of risk acceptance and degree of optimism in decision making process. Different risk acceptance level and/or optimism leads to different scheduling and sets of Pareto solutions from which the project manager may select his preferred options.     

Time–cost optimization: using GA and fuzzy sets theory for uncertainties in cost

Uncertainties should be considered in any time–cost trade‐off problems when minimizing project cost and duration, which leads to the so‐called stochastic time–cost trade‐off problem. A new approach to investigate stochastic time–cost trade‐off problems employing fuzzy logic theory is presented. The proposed approach fully embeds the fuzzy structure of the uncertainties in total direct cost into the model. An appropriate GA is used to develop a solution to the multi‐objective fuzzy time cost model. The accepted risk level of the project manager is defined through α cut approach for which a separate Pareto front with set of non‐dominated solutions has been developed. To compare the alternative set of options for any assumed project duration, associated fuzzy costs for different values of α cut are ranked employing two appropriate approaches for fuzzy costs comparison. The proposed models are applied to solve two benchmark test problems. It is shown that the models facilitate the decision‐making process by selecting specified risk levels and employing the associated Pareto front.     

Dynamic modeling of labor productivity in construction projects

The presence of labor with high productivity at each stage of a project's development plays a significant role in project success. This research presents a system dynamics (SD)-based approach to model labor productivity. The complex inter-related structure of different factors affecting labor productivity is modeled using system dynamics approach. The qualitative model of labor productivity is constructed using governing cause and effect feedback loops. Then, the relationships that existed between different factors are determined and the quantitative model of the labor productivity is built. Using the proposed SD model, the labor productivity is simulated considering the effects of all the influencing factors. The effect of labor productivity on different project performance measures is also assessed in terms of time and cost. Using the proposed model, the project manager may find the root causes of a decrease in productivity. Therefore, the labor productivity may be improved by implementation of proper solutions.     

A hybrid simulation approach for quantitatively analyzing the impact of facility size on construction projects

Sizing temporary facilities is a crucial task in construction site layout planning due to its significant impact on project productivity and cost. This paper describes a simulation-based approach for modeling the size of facilities that temporarily contain materials in construction projects. Different methods have been introduced for estimating the required size of this kind of facility; however, space limitations, particularly on congested sites, may not allow the planner to allocate the estimated space to the facilities. This study aims at quantitatively analyzing the impact of facility size on the project and modeling the managerial corrective actions to remedy the space shortage in facilities. To this end, a hybrid discrete-continuous simulation technique is adopted. Simulation is superior in modeling dynamic interactions between variables as well as modeling construction processes with inherent uncertainties. The combination of discrete and continuous simulation is used to enhance accuracy and model the project at both operational level (i.e., activity level with higher level of detail) to estimate production rate, and strategic level (i.e., macro level with lower level of detail) to account for some construction planning decisions such as material management variables. The novelty of this study is analyzing the impact of facility size on the project time and cost, while managerial actions taken to resolve space shortages are modeled, and interdependent influencing parameters of the different disciplines, such as site layout, material management, logistics, and construction process planning are integrated in a unified model. The applicability and suitability of the proposed approach is demonstrated in layout planning of a tunneling project site.     

基于风险分担的高速铁路投资风险评估模型研究

高速铁路建设项目在十一五期间取得了举世瞩目的成就,高铁运营里程跃升为全球第一。但中国高速铁路依然面临完工风险、运营风险、安全风险、技术风险等投资风险,由于高铁建设项目工程复杂、资金巨大,项目面临的投资风险按照一定比例由众多项目参与方分担,所以风险分担是高铁建设项目风险管理的起点。从风险分担入手,利用多目标规划方法找到最佳风险分担方案,并同项目实际风险分担方案比较,获得高速铁路建设项目风险评价指标体系。运用层次分析法确定各指标权重,利用综合评价法得到高速铁路建设项目投资风险评估值,最终确定该项目的风险水平。     

Model-based dynamic resource management for construction projects

Excess resource idling can result in cost overruns, while low resource coverage or long lead-time in resource acquisition can delay the project schedule. Therefore, systematically managing this tradeoff is critical to ensure project delivery in time and within budget. In addition, to provide practically useful guidelines and tools, the dynamic construction process needs to be realistically represented. As an effort to address these issues, a model-based dynamic approach is proposed for construction resource management. The dynamics of construction progress and the tradeoff with resource coverage are identified. Then, the dynamic resource management model that has been developed using system dynamics is described. By simulating the model with heuristic and industry data, the effect of resource coverage on project performance is quantified and policy implications are obtained for dynamic resource management. Finally, the use of the model as an automated tool is demonstrated.     

Fuzzy adaptive decision making model for selection balanced risk allocation

The unbalanced allocation of risks among the contracting parties is an important decision leading to increase of the total cost of a specific project and affects the overall relationship between the contracting parties. Due to common risk allocation decision-making process is based on experiential knowledge, is subjective and implicit. This paper presents a fuzzy adaptive decision making model for selection of balanced risk allocation which transforms the linguistic principles and experiential expert knowledge into a more usable and systematic quantitative-based analysis by using the fuzzy logic. The objectives of balanced risk allocation are developed based on the concept of Competence-Tendency trade-off. The proposed model integrates fuzzy logic qualitative approach and analytic hierarchy process (AHP) adaptive capabilities to evaluate allocation of project risks and determine best party to bear each one. Results from this model show its high capability in addressing most proper risk allocation with least contingency applied to the owner.     

Study on construction material allocation policies: A simulation optimization method

Due to uncertainty in both demand and supply, material shortages are difficult to completely avoid. To reduce the effect on the schedule and cost performance of construction projects, managers should allocate limited material among activities effectively. Motivated by observations of construction practices, this paper investigates the integration of supply logistics and site logistics issues and develops a framework to model inventory replenishment and allocation decisions jointly. On the basis of the activity feature information (e.g., schedule, cost, and demand), we propose five allocation policies to support the integrated inventory management process: schedule-based, cost-based, demand-based, schedule-cost-based, and schedule-demand-based policies. Meanwhile, a genetic algorithm (GA)-based simulation optimization method is utilized to solve the integrated inventory model and find the optimal inventory level under a given allocation policy. Based on a large set of fictitious project networks with different path difference (PD), a computational analysis is conducted to make detailed interpolicy comparisons. It is shown that for a project network with a small (or large) PD value, the schedule-based (or schedule-cost-based) policy is the most appropriate choice.     

EPC模式全生命周期视角的风险系统动力学研究

EPC工程总承包模式具有投资效益高、总成本低、设计与施工协调等优势,但同时其投资规模大、采购成本高、前期工作量大的特点为项目的实施带来了相当大的潜在风险。项目管理者要避免工程风险带来的不利影响,就必须熟悉风险在工程全生命周期下的动态变化以及影响机制,并采取有效措施来降低风险的发生。系统动力学仿真模型是诊断和分析多因素风险成因的方法,可有效地处理相互作用的、动态的项目风险。基于EPC模式全生命周期视角,运用Vensim PLE软件绘制出风险全过程结构图,构建EPC模式风险系统动力学（System Dynamics）模型,分析各影响因子间的因果关系及其内在联系,对系统风险反馈信息以及仿真模拟进行分析,从而为项目管理者提供决策依据,降低风险带来的不利影响,提升管理水平。     

Using fuzzy multiple criteria decision making approach to enhance risk assessment for metropolitan construction projects

The undertaking of construction projects in metropolitan areas is a risky, competitive, and dynamic proposition requiring a reliable risk assessment model for adequate planning. This study employs a fuzzy multiple criteria decision making (FMCDM) approach to systematically assess risk for a metropolitan construction project. Consistent fuzzy preference relations (CFPR) are used to measure and investigate the relative impact on project performance of twenty identified risk factors included in four risk dimensions. The fuzzy multiple attributes direct rating (FMADR) approach is employed to analyze the occurrence probability of multiple risk factors. Furthermore, the level of risk for the overall project caused by individual risk factor is evaluated with the synthesized analysis of the relative impacts and probability of occurrence. The implementation of FMCDM makes the proposed risk assessment approach more reliable and practical than the traditional statistical approach. The proposed approach can be employed to effectively evaluate the overall project risk, and can be benefited to efficiently identify significant risks of a metropolitan construction project.     

Schedule risk analysis of infrastructure projects: A hybrid dynamic approach

Schedule risk is a major concern in infrastructure project management. Existing studies have proposed several models for schedule risk analysis, but few efforts have been made on the dynamics and uncertainty of risks and the generality and practicability of the model. To fill the research gaps, this study develops a hybrid dynamic approach for investigating the effect of risks on infrastructure project schedule performance. This approach combines system dynamics (SD) and discrete event simulation (DES) which have mainly been used to analyze the macroscopic and microcosmic construction issues in isolation, respectively. The model is then verified by data which is collected from a bridge construction project. As an application example, the effect of four selected risks on the schedule was explored. The results show that the proposed SD-DES model could be ease of modifying the model to reflect real situation, performing various sensitivity and uncertainty analysis, and showing simulation results more effectively.     

基于不确定性因素的水利工程信息系统进度计划风险模型

进度计划风险控制是水利工程项目管理信息化实施目标的重要内容之一,对项目成本目标和质量目标的实现起到决定性作用。水利工程项目管理信息化进度计划受确定性和不确定双重因素的影响,进度计划表现出一定的随机性。基于水利工程项目群,分析了人为、环境和政策等不确定性因素对水利工程信息化进度计划的影响,并构建进度计划风险模型,通过蒙特卡洛方法对模型进行仿真性实验,验证了模型的有效性。     

基于链路和项目特征的地铁车站进度管理研究

为了解决潜在风险因素对地铁车站施工进度的制约,提高地铁车站项目关键链缓冲区设置的有效性,引入关键链技术,在其缓冲区设置时综合考虑链路和项目特征不确定性因素。首先,分析、量化链路不确定因素对地铁车站项目进度的影响,同时,采用WBS工作分解法和风险检查表法,识别地铁车站施工项目的进度不确定性因素;然后,结合链路和项目特征不确定因素,建立不确定性指标体系,采用改进的灰色关联分析法确定安全系数,计算缓冲区大小,并通过西安S地铁车站项目实例加以验证。最后将新方法结果与剪贴粘贴法、根方差法得到的结果进行对比分析。研究结果表明,此方法得到的关键链缓冲更为合理、稳定,可以有效缩短项目工期。